[INFO] fetching crate nnapi-sys 0.1.1...
[INFO] documenting nnapi-sys-0.1.1 against try#a394c9cd9ec93787f09a7ac445b14cc674a94549 for pr-151918-2
[INFO] extracting crate nnapi-sys 0.1.1 into /workspace/builds/worker-2-tc2/source
[INFO] started tweaking crates.io crate nnapi-sys 0.1.1
[INFO] finished tweaking crates.io crate nnapi-sys 0.1.1
[INFO] tweaked toml for crates.io crate nnapi-sys 0.1.1 written to /workspace/builds/worker-2-tc2/source/Cargo.toml
[INFO] validating manifest of crates.io crate nnapi-sys 0.1.1 on toolchain a394c9cd9ec93787f09a7ac445b14cc674a94549
[INFO] running `Command { std: CARGO_HOME="/workspace/cargo-home" RUSTUP_HOME="/workspace/rustup-home" "/workspace/cargo-home/bin/cargo" "+a394c9cd9ec93787f09a7ac445b14cc674a94549" "metadata" "--manifest-path" "Cargo.toml" "--no-deps", kill_on_drop: false }`
[INFO] crate crates.io crate nnapi-sys 0.1.1 already has a lockfile, it will not be regenerated
[INFO] running `Command { std: CARGO_HOME="/workspace/cargo-home" RUSTUP_HOME="/workspace/rustup-home" "/workspace/cargo-home/bin/cargo" "+a394c9cd9ec93787f09a7ac445b14cc674a94549" "fetch" "--manifest-path" "Cargo.toml", kill_on_drop: false }`
[INFO] [stderr]     Blocking waiting for file lock on package cache
[INFO] [stderr]     Blocking waiting for file lock on package cache
[INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-2-tc2/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-2-tc2/source:/opt/rustwide/workdir:ro,Z" "-v" "/var/lib/crater-agent-workspace/cargo-home:/opt/rustwide/cargo-home:ro,Z" "-v" "/var/lib/crater-agent-workspace/rustup-home:/opt/rustwide/rustup-home:ro,Z" "-e" "SOURCE_DIR=/opt/rustwide/workdir" "-e" "CARGO_TARGET_DIR=/opt/rustwide/target" "-e" "CARGO_HOME=/opt/rustwide/cargo-home" "-e" "RUSTUP_HOME=/opt/rustwide/rustup-home" "-w" "/opt/rustwide/workdir" "-m" "1610612736" "--user" "0:0" "--network" "none" "ghcr.io/rust-lang/crates-build-env/linux@sha256:61361fe0aef631f17e9d025a70c5a647956f8c671dd02950a60ad3f5cc5526d7" "/opt/rustwide/cargo-home/bin/cargo" "+a394c9cd9ec93787f09a7ac445b14cc674a94549" "metadata" "--no-deps" "--format-version=1", kill_on_drop: false }`
[INFO] [stdout] 5b93549105914824071ed561e2cfd1e22d3186a68ef01a61b67a040793db6a73
[INFO] running `Command { std: "docker" "start" "-a" "5b93549105914824071ed561e2cfd1e22d3186a68ef01a61b67a040793db6a73", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "inspect" "5b93549105914824071ed561e2cfd1e22d3186a68ef01a61b67a040793db6a73", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "rm" "-f" "5b93549105914824071ed561e2cfd1e22d3186a68ef01a61b67a040793db6a73", kill_on_drop: false }`
[INFO] [stdout] 5b93549105914824071ed561e2cfd1e22d3186a68ef01a61b67a040793db6a73
[INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-2-tc2/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-2-tc2/source:/opt/rustwide/workdir:ro,Z" "-v" "/var/lib/crater-agent-workspace/cargo-home:/opt/rustwide/cargo-home:ro,Z" "-v" "/var/lib/crater-agent-workspace/rustup-home:/opt/rustwide/rustup-home:ro,Z" "-e" "SOURCE_DIR=/opt/rustwide/workdir" "-e" "CARGO_TARGET_DIR=/opt/rustwide/target" "-e" "CARGO_INCREMENTAL=0" "-e" "RUST_BACKTRACE=full" "-e" "RUSTFLAGS=--cap-lints=forbid" "-e" "RUSTDOCFLAGS=--cap-lints=forbid" "-e" "CARGO_HOME=/opt/rustwide/cargo-home" "-e" "RUSTUP_HOME=/opt/rustwide/rustup-home" "-w" "/opt/rustwide/workdir" "-m" "1610612736" "--user" "0:0" "--network" "none" "ghcr.io/rust-lang/crates-build-env/linux@sha256:61361fe0aef631f17e9d025a70c5a647956f8c671dd02950a60ad3f5cc5526d7" "/opt/rustwide/cargo-home/bin/cargo" "+a394c9cd9ec93787f09a7ac445b14cc674a94549" "doc" "--frozen" "--no-deps" "--document-private-items" "--message-format=json", kill_on_drop: false }`
[INFO] [stdout] 6d7dafc2146bb12114bee71de02e644a7c26a14a1d1f0e8225e5093ddd8b302f
[INFO] running `Command { std: "docker" "start" "-a" "6d7dafc2146bb12114bee71de02e644a7c26a14a1d1f0e8225e5093ddd8b302f", kill_on_drop: false }`
[INFO] [stderr]  Documenting nnapi-sys v0.1.1 (/opt/rustwide/workdir)
[INFO] [stdout] warning: unresolved link to `channel`
[INFO] [stdout]    --> src/neural_networks.rs:696:13
[INFO] [stdout]     |
[INFO] [stdout] 696 | ... = " Performs a 2-D convolution operation.\n\n ...ter_scale\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
[INFO] [stdout]                                                                                         ^^^^^^^
[INFO] [stdout]     = note: no item named `channel` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout]     = note: `#[warn(rustdoc::broken_intra_doc_links)]` on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `depth_out`
[INFO] [stdout]    --> src/neural_networks.rs:696:13
[INFO] [stdout]     |
[INFO] [stdout] 696 | ... = " Performs a 2-D convolution operation.\n\n ...ter_scale\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
[INFO] [stdout]                                          ^^^^^^^^^
[INFO] [stdout]     = note: no item named `depth_out` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:696:13
[INFO] [stdout]     |
[INFO] [stdout] 696 | ... = " Performs a 2-D convolution operation.\n\n ...ter_scale\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  bias_scale[i] = input_scale * filter_scale[i].
[INFO] [stdout]                             ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:696:13
[INFO] [stdout]     |
[INFO] [stdout] 696 | ... = " Performs a 2-D convolution operation.\n\n ...ter_scale\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  bias_scale[i] = input_scale * filter_scale[i].
[INFO] [stdout]                                                             ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `channel`
[INFO] [stdout]    --> src/neural_networks.rs:698:13
[INFO] [stdout]     |
[INFO] [stdout] 698 | ... = " Performs a depthwise 2-D convolution opera...ter_scale\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
[INFO] [stdout]                                                                                         ^^^^^^^
[INFO] [stdout]     = note: no item named `channel` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `depth_out`
[INFO] [stdout]    --> src/neural_networks.rs:698:13
[INFO] [stdout]     |
[INFO] [stdout] 698 | ... = " Performs a depthwise 2-D convolution opera...ter_scale\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
[INFO] [stdout]                                          ^^^^^^^^^
[INFO] [stdout]     = note: no item named `depth_out` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:698:13
[INFO] [stdout]     |
[INFO] [stdout] 698 | ... = " Performs a depthwise 2-D convolution opera...ter_scale\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  bias_scale[i] = input_scale * filter_scale[i].
[INFO] [stdout]                             ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:698:13
[INFO] [stdout]     |
[INFO] [stdout] 698 | ... = " Performs a depthwise 2-D convolution opera...ter_scale\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  bias_scale[i] = input_scale * filter_scale[i].
[INFO] [stdout]                                                             ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `3`
[INFO] [stdout]    --> src/neural_networks.rs:704:13
[INFO] [stdout]     |
[INFO] [stdout] 704 | ... = " Looks up sub-tensors in the input tensor.\...s input1.\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             Lookups has shape of [3], all three values found in Lookups are
[INFO] [stdout]                                   ^
[INFO] [stdout]     = note: no item named `3` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_units`
[INFO] [stdout]    --> src/neural_networks.rs:708:13
[INFO] [stdout]     |
[INFO] [stdout] 708 | ... = " Denotes a fully (densely) connected layer,...er_scale.\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             * 2: A 1-D tensor, of shape [num_units], specifying the bias. For input
[INFO] [stdout]                                          ^^^^^^^^^
[INFO] [stdout]     = note: no item named `num_units` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `40`
[INFO] [stdout]    --> src/neural_networks.rs:710:13
[INFO] [stdout]     |
[INFO] [stdout] 710 | ... = " Looks up sub-tensors in the input tensor u...therwise.\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             Keys should have a shape of [40]. If Lookups tensor has shape
[INFO] [stdout]                                          ^^
[INFO] [stdout]     = note: no item named `40` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `3`
[INFO] [stdout]    --> src/neural_networks.rs:710:13
[INFO] [stdout]     |
[INFO] [stdout] 710 | ... = " Looks up sub-tensors in the input tensor u...therwise.\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             of [3], three slices are being concatenated, so the resulting tensor
[INFO] [stdout]                 ^
[INFO] [stdout]     = note: no item named `3` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `k`
[INFO] [stdout]    --> src/neural_networks.rs:710:13
[INFO] [stdout]     |
[INFO] [stdout] 710 | ... = " Looks up sub-tensors in the input tensor u...therwise.\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  shape [ k ].
[INFO] [stdout]                         ^^^
[INFO] [stdout]     = note: no item named `k` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `n`
[INFO] [stdout]    --> src/neural_networks.rs:710:1706
[INFO] [stdout]     |
[INFO] [stdout] 710 | ...NETWORKS_TENSOR_INT32} tensor with shape\n      [ n ]; Keys and Values pair represent a map, i.e., the ith element\n      in Key...
[INFO] [stdout]     |                                                      ^ no item named `n` in scope
[INFO] [stdout]     |
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:710:13
[INFO] [stdout]     |
[INFO] [stdout] 710 | ... = " Looks up sub-tensors in the input tensor u...therwise.\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  in Keys (Keys[i]) is the key to select the ith sub-tensor in Values
[INFO] [stdout]                                ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:710:13
[INFO] [stdout]     |
[INFO] [stdout] 710 | ... = " Looks up sub-tensors in the input tensor u...therwise.\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  (Values[i]), where 0 <= i <= n-1. Keys tensor *MUST* be sorted in
[INFO] [stdout]                          ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `k`
[INFO] [stdout]    --> src/neural_networks.rs:710:13
[INFO] [stdout]     |
[INFO] [stdout] 710 | ... = " Looks up sub-tensors in the input tensor u...therwise.\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             * 1: Hits. A boolean tensor with shape [ k ] indicates whether the lookup
[INFO] [stdout]                                                     ^^^
[INFO] [stdout]     = note: no item named `k` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `0`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Tensor[0].Dim[0]: Number of hash functions.
[INFO] [stdout]                         ^
[INFO] [stdout]     = note: no item named `0` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `0`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Tensor[0].Dim[0]: Number of hash functions.
[INFO] [stdout]                                ^
[INFO] [stdout]     = note: no item named `0` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `0`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Tensor[0].Dim[1]: Number of projected output bits generated by each
[INFO] [stdout]                         ^
[INFO] [stdout]     = note: no item named `0` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Tensor[0].Dim[1]: Number of projected output bits generated by each
[INFO] [stdout]                                ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `0`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Tensor[0].Dim[1] + ceil(log2(Tensor[0].Dim[0])) <= 32
[INFO] [stdout]                         ^
[INFO] [stdout]     = note: no item named `0` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Tensor[0].Dim[1] + ceil(log2(Tensor[0].Dim[0])) <= 32
[INFO] [stdout]                                ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `0`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Tensor[0].Dim[1] + ceil(log2(Tensor[0].Dim[0])) <= 32
[INFO] [stdout]                                                      ^
[INFO] [stdout]     = note: no item named `0` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `0`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Tensor[0].Dim[1] + ceil(log2(Tensor[0].Dim[0])) <= 32
[INFO] [stdout]                                                             ^
[INFO] [stdout]     = note: no item named `0` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Tensor[1].Dim[0] == Tensor[2].Dim[0]
[INFO] [stdout]                         ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `0`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Tensor[1].Dim[0] == Tensor[2].Dim[0]
[INFO] [stdout]                                ^
[INFO] [stdout]     = note: no item named `0` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `2`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Tensor[1].Dim[0] == Tensor[2].Dim[0]
[INFO] [stdout]                                             ^
[INFO] [stdout]     = note: no item named `2` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `0`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Tensor[1].Dim[0] == Tensor[2].Dim[0]
[INFO] [stdout]                                                    ^
[INFO] [stdout]     = note: no item named `0` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `0`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Output.Dim == { Tensor[0].Dim[0] }
[INFO] [stdout]                                         ^
[INFO] [stdout]     = note: no item named `0` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `0`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Output.Dim == { Tensor[0].Dim[0] }
[INFO] [stdout]                                                ^
[INFO] [stdout]     = note: no item named `0` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `0`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Output.Dim == { Tensor[0].Dim[0] * Tensor[0].Dim[1] }
[INFO] [stdout]                                         ^
[INFO] [stdout]     = note: no item named `0` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `0`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Output.Dim == { Tensor[0].Dim[0] * Tensor[0].Dim[1] }
[INFO] [stdout]                                                ^
[INFO] [stdout]     = note: no item named `0` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `0`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Output.Dim == { Tensor[0].Dim[0] * Tensor[0].Dim[1] }
[INFO] [stdout]                                                            ^
[INFO] [stdout]     = note: no item named `0` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:720:13
[INFO] [stdout]     |
[INFO] [stdout] 720 | ... = " Projects an input to a bit vector via loca...arse projections was added in API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Output.Dim == { Tensor[0].Dim[0] * Tensor[0].Dim[1] }
[INFO] [stdout]                                                                   ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_units`
[INFO] [stdout]    --> src/neural_networks.rs:722:13
[INFO] [stdout]     |
[INFO] [stdout] 722 | ... = " Performs a single time step in a Long Shor...)” value.\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  A 1-D tensor of shape [num_units].
[INFO] [stdout]                                         ^^^^^^^^^
[INFO] [stdout]     = note: no item named `num_units` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `output_size`
[INFO] [stdout]    --> src/neural_networks.rs:722:13
[INFO] [stdout]     |
[INFO] [stdout] 722 | ... = " Performs a single time step in a Long Shor...)” value.\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  A 1-D tensor of shape [output_size].
[INFO] [stdout]                                         ^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `output_size` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_units`
[INFO] [stdout]    --> src/neural_networks.rs:722:13
[INFO] [stdout]     |
[INFO] [stdout] 722 | ... = " Performs a single time step in a Long Shor...)” value.\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  A 1-D tensor of shape [num_units]. Used to rescale normalized inputs
[INFO] [stdout]                                         ^^^^^^^^^
[INFO] [stdout]     = note: no item named `num_units` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_units`
[INFO] [stdout]    --> src/neural_networks.rs:738:13
[INFO] [stdout]     |
[INFO] [stdout] 738 | ... = " A basic recurrent neural network layer.\n\...te value.\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  A 1-D tensor of shape [num_units].
[INFO] [stdout]                                         ^^^^^^^^^
[INFO] [stdout]     = note: no item named `num_units` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_units`
[INFO] [stdout]    --> src/neural_networks.rs:744:13
[INFO] [stdout]     |
[INFO] [stdout] 744 | ... = " SVDF op is a kind of stateful layer derive...m_units].\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  An optional 1-D tensor of shape [num_units].
[INFO] [stdout]                                                   ^^^^^^^^^
[INFO] [stdout]     = note: no item named `num_units` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `batch`
[INFO] [stdout]    --> src/neural_networks.rs:748:13
[INFO] [stdout]     |
[INFO] [stdout] 748 | ... = " BatchToSpace for N-dimensional tensors.\n\...s input0.\n\n Available since API level 28."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             dimensions of shape block_shape + [batch], interleaves these blocks back
[INFO] [stdout]                                                ^^^^^
[INFO] [stdout]     = note: no item named `batch` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:752:13
[INFO] [stdout]     |
[INFO] [stdout] 752 | ... = " Computes the mean of elements across dimen...e is [1].\n\n Available since API level 28."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  shape is [1].
[INFO] [stdout]                            ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:754:13
[INFO] [stdout]     |
[INFO] [stdout] 754 | ... = " Pads a tensor.\n\n This operation pads a t...cal zero.\n\n Available since API level 28."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                      output0.dimension[i] =
[INFO] [stdout]                                        ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:754:13
[INFO] [stdout]     |
[INFO] [stdout] 754 | ... = " Pads a tensor.\n\n This operation pads a t...cal zero.\n\n Available since API level 28."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                          padding[i, 0] + input0.dimension[i] + padding[i, 1]
[INFO] [stdout]                                                           ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:758:13
[INFO] [stdout]     |
[INFO] [stdout] 758 | ... = " Removes dimensions of size 1 from the shap...e is [1].\n\n Available since API level 28."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  output shape is [1].
[INFO] [stdout]                                   ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:760:13
[INFO] [stdout]     |
[INFO] [stdout] 760 | ... = " Extracts a strided slice of a tensor.\n\n ...e is [1].\n\n Available since API level 28."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  of begin_mask is set, begin[i] is ignored and the fullest possible
[INFO] [stdout]                                              ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:760:13
[INFO] [stdout]     |
[INFO] [stdout] 760 | ... = " Extracts a strided slice of a tensor.\n\n ...e is [1].\n\n Available since API level 28."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  end_mask is set, end[i] is ignored and the fullest possible range in
[INFO] [stdout]                                       ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:760:13
[INFO] [stdout]     |
[INFO] [stdout] 760 | ... = " Extracts a strided slice of a tensor.\n\n ...e is [1].\n\n Available since API level 28."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  begin[i]. In this case, the ith specification must define a
[INFO] [stdout]                        ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:760:13
[INFO] [stdout]     |
[INFO] [stdout] 760 | ... = " Extracts a strided slice of a tensor.\n\n ...e is [1].\n\n Available since API level 28."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  slice of size 1, e.g. begin[i] = x, end[i] = x + 1.
[INFO] [stdout]                                              ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:760:13
[INFO] [stdout]     |
[INFO] [stdout] 760 | ... = " Extracts a strided slice of a tensor.\n\n ...e is [1].\n\n Available since API level 28."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  slice of size 1, e.g. begin[i] = x, end[i] = x + 1.
[INFO] [stdout]                                                          ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:760:13
[INFO] [stdout]     |
[INFO] [stdout] 760 | ... = " Extracts a strided slice of a tensor.\n\n ...e is [1].\n\n Available since API level 28."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  shape is [1].
[INFO] [stdout]                            ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:764:13
[INFO] [stdout]     |
[INFO] [stdout] 764 | ... = " Transposes the input tensor, permuting the...s input0.\n\n Available since API level 28."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             perm[i]. If perm is not given, it is set to (n-1...0), where n is the
[INFO] [stdout]                  ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:768:13
[INFO] [stdout]     |
[INFO] [stdout] 768 | ... = " Returns the index of the largest element a...e is [1].\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  If input is 1-dimensional, the output shape is [1].
[INFO] [stdout]                                                                  ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:770:13
[INFO] [stdout]     |
[INFO] [stdout] 770 | ... = " Returns the index of the smallest element ...e is [1].\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  If input is 1-dimensional, the output shape is [1].
[INFO] [stdout]                                                                  ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_rois`
[INFO] [stdout]    --> src/neural_networks.rs:772:13
[INFO] [stdout]     |
[INFO] [stdout] 772 | ... = " Transform axis-aligned bounding box propos...ust be 0.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  [num_rois], specifying the batch index of each box. Boxes with
[INFO] [stdout]                   ^^^^^^^^
[INFO] [stdout]     = note: no item named `num_rois` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `fw_num_units`
[INFO] [stdout]    --> src/neural_networks.rs:774:13
[INFO] [stdout]     |
[INFO] [stdout] 774 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  A 1-D tensor of shape [fw_num_units].
[INFO] [stdout]                                         ^^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `fw_num_units` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `fw_num_units`
[INFO] [stdout]    --> src/neural_networks.rs:774:13
[INFO] [stdout]     |
[INFO] [stdout] 774 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                   A 1-D tensor of shape [fw_num_units].
[INFO] [stdout]                                          ^^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `fw_num_units` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `fw_output_size`
[INFO] [stdout]    --> src/neural_networks.rs:774:13
[INFO] [stdout]     |
[INFO] [stdout] 774 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                   A 1-D tensor of shape [fw_output_size].
[INFO] [stdout]                                          ^^^^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `fw_output_size` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `bw_num_units`
[INFO] [stdout]    --> src/neural_networks.rs:774:13
[INFO] [stdout]     |
[INFO] [stdout] 774 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                   A 1-D tensor of shape [bw_num_units].
[INFO] [stdout]                                          ^^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `bw_num_units` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `bw_output_size`
[INFO] [stdout]    --> src/neural_networks.rs:774:13
[INFO] [stdout]     |
[INFO] [stdout] 774 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                   A 1-D tensor of shape [bw_output_size].
[INFO] [stdout]                                          ^^^^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `bw_output_size` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `fw_num_units`
[INFO] [stdout]    --> src/neural_networks.rs:774:13
[INFO] [stdout]     |
[INFO] [stdout] 774 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                   A 1-D tensor of shape [fw_num_units]. Used to rescale normalized inputs
[INFO] [stdout]                                          ^^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `fw_num_units` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `bw_num_units`
[INFO] [stdout]    --> src/neural_networks.rs:774:13
[INFO] [stdout]     |
[INFO] [stdout] 774 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                   A 1-D tensor of shape [bw_num_units]. Used to rescale normalized inputs
[INFO] [stdout]                                          ^^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `bw_num_units` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `s`
[INFO] [stdout]    --> src/neural_networks.rs:776:13
[INFO] [stdout]     |
[INFO] [stdout] 776 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]               fw_outputs[s] = fw_state = activation(inputs[s] * fw_input_weights’ +
[INFO] [stdout]                          ^
[INFO] [stdout]     = note: no item named `s` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `s`
[INFO] [stdout]    --> src/neural_networks.rs:776:13
[INFO] [stdout]     |
[INFO] [stdout] 776 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]               fw_outputs[s] = fw_state = activation(inputs[s] * fw_input_weights’ +
[INFO] [stdout]                                                            ^
[INFO] [stdout]     = note: no item named `s` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `t`
[INFO] [stdout]    --> src/neural_networks.rs:776:13
[INFO] [stdout]     |
[INFO] [stdout] 776 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]               bw_outputs[t] = bw_state = activation(inputs[t] * bw_input_weights’ +
[INFO] [stdout]                          ^
[INFO] [stdout]     = note: no item named `t` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `t`
[INFO] [stdout]    --> src/neural_networks.rs:776:13
[INFO] [stdout]     |
[INFO] [stdout] 776 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]               bw_outputs[t] = bw_state = activation(inputs[t] * bw_input_weights’ +
[INFO] [stdout]                                                            ^
[INFO] [stdout]     = note: no item named `t` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `fwNumUnits`
[INFO] [stdout]    --> src/neural_networks.rs:776:13
[INFO] [stdout]     |
[INFO] [stdout] 776 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  A 1-D tensor of shape [fwNumUnits].
[INFO] [stdout]                                         ^^^^^^^^^^
[INFO] [stdout]     = note: no item named `fwNumUnits` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `bwNumUnits`
[INFO] [stdout]    --> src/neural_networks.rs:776:13
[INFO] [stdout]     |
[INFO] [stdout] 776 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  A 1-D tensor of shape [bwNumUnits].
[INFO] [stdout]                                         ^^^^^^^^^^
[INFO] [stdout]     = note: no item named `bwNumUnits` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_rois`
[INFO] [stdout]    --> src/neural_networks.rs:778:13
[INFO] [stdout]     |
[INFO] [stdout] 778 | ... = " Greedily selects a subset of bounding boxe...together.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  [num_rois], specifying the batch index of each box. Boxes with
[INFO] [stdout]                   ^^^^^^^^
[INFO] [stdout]     = note: no item named `num_rois` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_output_rois`
[INFO] [stdout]    --> src/neural_networks.rs:778:13
[INFO] [stdout]     |
[INFO] [stdout] 778 | ... = " Greedily selects a subset of bounding boxe...together.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  [num_output_rois], specifying the score of each output box. The boxes
[INFO] [stdout]                   ^^^^^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `num_output_rois` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_output_rois`
[INFO] [stdout]    --> src/neural_networks.rs:778:13
[INFO] [stdout]     |
[INFO] [stdout] 778 | ... = " Greedily selects a subset of bounding boxe...together.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  [num_output_rois], specifying the class of each output box. The
[INFO] [stdout]                   ^^^^^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `num_output_rois` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_output_rois`
[INFO] [stdout]    --> src/neural_networks.rs:778:13
[INFO] [stdout]     |
[INFO] [stdout] 778 | ... = " Greedily selects a subset of bounding boxe...together.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  [num_output_rois], specifying the batch index of each box. Boxes
[INFO] [stdout]                   ^^^^^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `num_output_rois` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `batches`
[INFO] [stdout]    --> src/neural_networks.rs:784:13
[INFO] [stdout]     |
[INFO] [stdout] 784 | ... = " Apply postprocessing steps to bounding box...ch batch.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             * 3: An 1-D {@link ANEURALNETWORKS_TENSOR_INT32} tensor, of shape [batches],
[INFO] [stdout]                                                                                ^^^^^^^
[INFO] [stdout]     = note: no item named `batches` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `:axis`
[INFO] [stdout]    --> src/neural_networks.rs:792:109
[INFO] [stdout]     |
[INFO] [stdout] 792 | ...tput tensor with shape\n     input0.dimension[:axis] + indices.dimension + input0.dimension[axis + 1:]\n where:\n     # Vector i...
[INFO] [stdout]     |                                                  ^^^^^ no item named `:axis` in scope
[INFO] [stdout]     |
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:792:13
[INFO] [stdout]     |
[INFO] [stdout] 792 | ... = " Gathers values along an axis.\n\n Produces...s input0.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                   input0[a_0, ..., a_n, indices[i], b_0, ..., b_n]
[INFO] [stdout]                                                 ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_output_rois`
[INFO] [stdout]    --> src/neural_networks.rs:794:13
[INFO] [stdout]     |
[INFO] [stdout] 794 | ... = " Generate aixs-aligned bounding box proposa...together.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  [num_output_rois], specifying the score of each output box.
[INFO] [stdout]                   ^^^^^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `num_output_rois` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_output_rois`
[INFO] [stdout]    --> src/neural_networks.rs:794:13
[INFO] [stdout]     |
[INFO] [stdout] 794 | ... = " Generate aixs-aligned bounding box proposa...together.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  [num_output_rois], specifying the batch index of each box. Boxes
[INFO] [stdout]                   ^^^^^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `num_output_rois` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `channel`
[INFO] [stdout]    --> src/neural_networks.rs:800:13
[INFO] [stdout]     |
[INFO] [stdout] 800 | ... = " Performs a grouped 2-D convolution operati...eroPoint.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
[INFO] [stdout]                                                                                         ^^^^^^^
[INFO] [stdout]     = note: no item named `channel` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `depth_out`
[INFO] [stdout]    --> src/neural_networks.rs:800:13
[INFO] [stdout]     |
[INFO] [stdout] 800 | ... = " Performs a grouped 2-D convolution operati...eroPoint.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
[INFO] [stdout]                                          ^^^^^^^^^
[INFO] [stdout]     = note: no item named `depth_out` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:800:13
[INFO] [stdout]     |
[INFO] [stdout] 800 | ... = " Performs a grouped 2-D convolution operati...eroPoint.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  bias_scale[i] = input_scale * filter_scale[i].
[INFO] [stdout]                             ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:800:13
[INFO] [stdout]     |
[INFO] [stdout] 800 | ... = " Performs a grouped 2-D convolution operati...eroPoint.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  bias_scale[i] = input_scale * filter_scale[i].
[INFO] [stdout]                                                             ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:828:13
[INFO] [stdout]     |
[INFO] [stdout] 828 | ... = " Pads a tensor with the given constant valu...s input0.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                      output0.dimension[i] =
[INFO] [stdout]                                        ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:828:13
[INFO] [stdout]     |
[INFO] [stdout] 828 | ... = " Pads a tensor with the given constant valu...s input0.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                          padding[i, 0] + input0.dimension[i] + padding[i, 1]
[INFO] [stdout]                                                           ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `outputSize`
[INFO] [stdout]    --> src/neural_networks.rs:836:13
[INFO] [stdout]     |
[INFO] [stdout] 836 | ... = " A version of quantized LSTM, using 16 bit ...8]\n      (scale = 1/128, zeroPoint = 128)."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  [outputSize] specifying the bias for the fully-connected layer
[INFO] [stdout]                   ^^^^^^^^^^
[INFO] [stdout]     = note: no item named `outputSize` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `2`
[INFO] [stdout]    --> src/neural_networks.rs:838:13
[INFO] [stdout]     |
[INFO] [stdout] 838 | ... = " Draws samples from a multinomial distribut... samples.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             * 2: A 1-D {@link ANEURALNETWORKS_TENSOR_INT32} tensor with shape [2],
[INFO] [stdout]                                                                                ^
[INFO] [stdout]     = note: no item named `2` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:840:13
[INFO] [stdout]     |
[INFO] [stdout] 840 | ... = " Reduces a tensor by computing the \"logica...e is [1].\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  shape is [1].
[INFO] [stdout]                            ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:842:13
[INFO] [stdout]     |
[INFO] [stdout] 842 | ... = " Reduces a tensor by computing the \"logica...e is [1].\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  shape is [1].
[INFO] [stdout]                            ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:844:13
[INFO] [stdout]     |
[INFO] [stdout] 844 | ... = " Reduces a tensor by computing the maximum ...s input0.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  shape is [1].
[INFO] [stdout]                            ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:846:13
[INFO] [stdout]     |
[INFO] [stdout] 846 | ... = " Reduces a tensor by computing the minimum ...s input0.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  shape is [1].
[INFO] [stdout]                            ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:848:13
[INFO] [stdout]     |
[INFO] [stdout] 848 | ... = " Reduces a tensor by multiplying elements a...e is [1].\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  shape is [1].
[INFO] [stdout]                            ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:850:13
[INFO] [stdout]     |
[INFO] [stdout] 850 | ... = " Reduces a tensor by summing elements along...e is [1].\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  shape is [1].
[INFO] [stdout]                            ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_rois`
[INFO] [stdout]    --> src/neural_networks.rs:852:13
[INFO] [stdout]     |
[INFO] [stdout] 852 | ... = " Select and scale the feature map of each r...eroPoint.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  [num_rois], specifying the batch index of each box. Boxes with
[INFO] [stdout]                   ^^^^^^^^
[INFO] [stdout]     = note: no item named `num_rois` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_rois`
[INFO] [stdout]    --> src/neural_networks.rs:854:13
[INFO] [stdout]     |
[INFO] [stdout] 854 | ... = " Select and scale the feature map of each r...s input0.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  [num_rois], specifying the batch index of each box. Boxes with
[INFO] [stdout]                   ^^^^^^^^
[INFO] [stdout]     = note: no item named `num_rois` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:858:13
[INFO] [stdout]     |
[INFO] [stdout] 858 | ... = " Using a tensor of booleans c and input ten...eroPoint.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             O[i] = C[i] ? x[i] : y[i].
[INFO] [stdout]               ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:858:13
[INFO] [stdout]     |
[INFO] [stdout] 858 | ... = " Using a tensor of booleans c and input ten...eroPoint.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             O[i] = C[i] ? x[i] : y[i].
[INFO] [stdout]                      ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:858:13
[INFO] [stdout]     |
[INFO] [stdout] 858 | ... = " Using a tensor of booleans c and input ten...eroPoint.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             O[i] = C[i] ? x[i] : y[i].
[INFO] [stdout]                             ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:858:13
[INFO] [stdout]     |
[INFO] [stdout] 858 | ... = " Using a tensor of booleans c and input ten...eroPoint.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             O[i] = C[i] ? x[i] : y[i].
[INFO] [stdout]                                    ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `channel`
[INFO] [stdout]    --> src/neural_networks.rs:872:13
[INFO] [stdout]     |
[INFO] [stdout] 872 | ... = " Performs the transpose of 2-D convolution ...eroPoint.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             * * each value scaling is separate and equal to input.scale * filter.scales[channel]).
[INFO] [stdout]                                                                                         ^^^^^^^
[INFO] [stdout]     = note: no item named `channel` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `depth_out`
[INFO] [stdout]    --> src/neural_networks.rs:872:13
[INFO] [stdout]     |
[INFO] [stdout] 872 | ... = " Performs the transpose of 2-D convolution ...eroPoint.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             * 2: A 1-D tensor, of shape [depth_out], specifying the bias. For input
[INFO] [stdout]                                          ^^^^^^^^^
[INFO] [stdout]     = note: no item named `depth_out` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:872:13
[INFO] [stdout]     |
[INFO] [stdout] 872 | ... = " Performs the transpose of 2-D convolution ...eroPoint.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  bias_scale[i] = input_scale * filter_scale[i].
[INFO] [stdout]                             ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `i`
[INFO] [stdout]    --> src/neural_networks.rs:872:13
[INFO] [stdout]     |
[INFO] [stdout] 872 | ... = " Performs the transpose of 2-D convolution ...eroPoint.\n\n Available since API level 29."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  bias_scale[i] = input_scale * filter_scale[i].
[INFO] [stdout]                                                             ^
[INFO] [stdout]     = note: no item named `i` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `s`
[INFO] [stdout]    --> src/neural_networks.rs:874:13
[INFO] [stdout]     |
[INFO] [stdout] 874 | ... = " A recurrent neural network specified by an...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]               outputs[s] = projection(state = activation(LSTMOp(inputs[s])))
[INFO] [stdout]                       ^
[INFO] [stdout]     = note: no item named `s` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `s`
[INFO] [stdout]    --> src/neural_networks.rs:874:13
[INFO] [stdout]     |
[INFO] [stdout] 874 | ... = " A recurrent neural network specified by an...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]               outputs[s] = projection(state = activation(LSTMOp(inputs[s])))
[INFO] [stdout]                                                                        ^
[INFO] [stdout]     = note: no item named `s` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_units`
[INFO] [stdout]    --> src/neural_networks.rs:874:13
[INFO] [stdout]     |
[INFO] [stdout] 874 | ... = " A recurrent neural network specified by an...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  A 1-D tensor of shape [num_units].
[INFO] [stdout]                                         ^^^^^^^^^
[INFO] [stdout]     = note: no item named `num_units` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `output_size`
[INFO] [stdout]    --> src/neural_networks.rs:874:13
[INFO] [stdout]     |
[INFO] [stdout] 874 | ... = " A recurrent neural network specified by an...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  A 1-D tensor of shape [output_size].
[INFO] [stdout]                                         ^^^^^^^^^^^
[INFO] [stdout]     = note: no item named `output_size` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `num_units`
[INFO] [stdout]    --> src/neural_networks.rs:874:13
[INFO] [stdout]     |
[INFO] [stdout] 874 | ... = " A recurrent neural network specified by an...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  A 1-D tensor of shape [num_units]. Used to rescale normalized inputs
[INFO] [stdout]                                         ^^^^^^^^^
[INFO] [stdout]     = note: no item named `num_units` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `s`
[INFO] [stdout]    --> src/neural_networks.rs:876:13
[INFO] [stdout]     |
[INFO] [stdout] 876 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]               outputs[s] = state = activation(inputs[s] * input_weights’ + state *
[INFO] [stdout]                       ^
[INFO] [stdout]     = note: no item named `s` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `s`
[INFO] [stdout]    --> src/neural_networks.rs:876:13
[INFO] [stdout]     |
[INFO] [stdout] 876 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]               outputs[s] = state = activation(inputs[s] * input_weights’ + state *
[INFO] [stdout]                                                      ^
[INFO] [stdout]     = note: no item named `s` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `numUnits`
[INFO] [stdout]    --> src/neural_networks.rs:876:13
[INFO] [stdout]     |
[INFO] [stdout] 876 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  A 1-D tensor of shape [numUnits].
[INFO] [stdout]                                         ^^^^^^^^
[INFO] [stdout]     = note: no item named `numUnits` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `numUnits`
[INFO] [stdout]    --> src/neural_networks.rs:880:13
[INFO] [stdout]     |
[INFO] [stdout] 880 | ... = " Quantized version of {@link ANEURALNETWORK...tputSize]\n\n Available since API level 30."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  Shape: [numUnits]
[INFO] [stdout]                          ^^^^^^^^
[INFO] [stdout]     = note: no item named `numUnits` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `numUnits`
[INFO] [stdout]    --> src/neural_networks.rs:880:13
[INFO] [stdout]     |
[INFO] [stdout] 880 | ... = " Quantized version of {@link ANEURALNETWORK...tputSize]\n\n Available since API level 30."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                   Shape: [numUnits]
[INFO] [stdout]                           ^^^^^^^^
[INFO] [stdout]     = note: no item named `numUnits` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `outputSize`
[INFO] [stdout]    --> src/neural_networks.rs:880:13
[INFO] [stdout]     |
[INFO] [stdout] 880 | ... = " Quantized version of {@link ANEURALNETWORK...tputSize]\n\n Available since API level 30."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                   Shape: [outputSize]
[INFO] [stdout]                           ^^^^^^^^^^
[INFO] [stdout]     = note: no item named `outputSize` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:882:13
[INFO] [stdout]     |
[INFO] [stdout] 882 | ... = " Executes one of the two referenced models ...ed model.\n\n Available since API level 30."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]             * 0: A value of type {@link ANEURALNETWORKS_TENSOR_BOOL8} and shape [1]
[INFO] [stdout]                                                                                  ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `1`
[INFO] [stdout]    --> src/neural_networks.rs:884:13
[INFO] [stdout]     |
[INFO] [stdout] 884 | ... = " Executes the body model until the conditio...the loop.\n\n Available since API level 30."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: the link appears in this line:
[INFO] [stdout]             
[INFO] [stdout]                  of {@link ANEURALNETWORKS_TENSOR_BOOL8} and shape [1].
[INFO] [stdout]                                                                     ^
[INFO] [stdout]     = note: no item named `1` in scope
[INFO] [stdout]     = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unresolved link to `channelDim`
[INFO] [stdout]     --> src/neural_networks.rs:1078:73
[INFO] [stdout]      |
[INFO] [stdout] 1078 |     #[doc = " The size of the scale array. Should be equal to dimension[channelDim] of the Operand."]
[INFO] [stdout]      |                                                                         ^^^^^^^^^^ no item named `channelDim` in scope
[INFO] [stdout]      |
[INFO] [stdout]      = help: to escape `[` and `]` characters, add '\' before them like `\[` or `\]`
[INFO] [stdout] 
[INFO] [stdout] 
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[INFO] [stdout]     --> src/neural_networks.rs:1391:13
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[INFO] [stdout] 1391 | ... = " Create an empty {@link ANeuralNetworksMod...turn ANEURALNETWORKS_NO_ERROR if successful."]
[INFO] [stdout]      |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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[INFO] [stdout]     --> src/neural_networks.rs:1399:778
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[INFO] [stdout] 1399 | ...nd must be referenced in exactly one of the following\n ways:<ul>\n    <li>It is identified as a model input with\n        {@li...
[INFO] [stdout]      |                                                                 ^^^^
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[INFO] [stdout]     --> src/neural_networks.rs:1484:41
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[INFO] [stdout] 1484 |     #[doc = " Destroy an execution.\n\n <p>The execution need not have been scheduled by a call to\n {@link ANeuralNetworksExecuti...
[INFO] [stdout]      |                                         ^^^
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[INFO] [stdout]    --> src/neural_networks.rs:708:197
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[INFO] [stdout] 708 | ... layer implements the operation:\n\n     outputs = activation(inputs * weights’ + bias)\n\n Supported tensor {@link OperandCode}...
[INFO] [stdout]     |                                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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[INFO] [stdout]    --> src/neural_networks.rs:722:13
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[INFO] [stdout] 722 | ... = " Performs a single time step in a Long Shor...)” value.\n\n Available since API level 27."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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[INFO] [stdout]    --> src/neural_networks.rs:722:4374
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[INFO] [stdout] 722 | ...on-CIFG implementation is based on:\n http://www.bioinf.jku.at/publications/older/2604.pdf\n S. Hochreiter and J. Schmidhuber. \...
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[INFO] [stdout] 722 |     #[doc = " Performs a single time step in a Long Short-Term Memory (LSTM) layer\n\n The LSTM operation is described by the following equations.\n\n \\f{eqnarray*}{\n i_t =& \\sigma(W_{xi}x_t+W_{hi}h_{t-1}+W_{ci}C_{t-1}+b_i) & \\\\\n f_t =& \\sigma(W_{xf}x_t+W_{hf}h_{t-1}+W_{cf}C_{t-1}+b_f) & \\\\\n C_t =& clip(f_t \\odot C_{t-1} + i_t \\odot\n        g(W_{xc}x_t+W_{hc}h_{t-1}+b_c),\\ t_{cell}) & \\\\\n o_t =& \\sigma(W_{xo}x_t+W_{ho}h_{t-1}+W_{co}C_t+b_o) & \\\\\n      & & \\\\\n      & clip(W_{proj}(o_t \\odot g(C_t))+b_{proj},\\ t_{proj})\n      & if\\ there\\ is\\ a\\ projection; \\\\\n h_t =& & \\\\\n      & o_t \\odot g(C_t) & otherwise. \\\\\n \\f}\n Where:\n * \\f$x_t\\f$ is the input,\n * \\f$i_t\\f$ is the input gate,\n * \\f$f_t\\f$ is the forget gate,\n * \\f$C_t\\f$ is the cell state,\n * \\f$o_t\\f$ is the output,\n * \\f$h_t\\f$ is the output state,\n * \\f$\\sigma\\f$ is the logistic sigmoid function,\n * \\f$g\\f$ is the cell input and cell output activation function, usually\n   \\f$tahn\\f$,\n * \\f$W_{xi}\\f$ is the input-to-input weight matrix,\n * \\f$W_{hi}\\f$ is the recurrent to input weight matrix,\n * \\f$W_{ci}\\f$ is the cell-to-input weight matrix,\n * \\f$b_i\\f$ is the input gate bias,\n * \\f$W_{xf}\\f$ is the input-to-forget weight matrix,\n * \\f$W_{hf}\\f$ is the recurrent-to-forget weight matrix,\n * \\f$W_{cf}\\f$ is the cell-to-forget weight matrix,\n * \\f$b_f\\f$ is the forget gate bias,\n * \\f$W_{xc}\\f$ is the input-to-cell weight matrix,\n * \\f$W_{hc}\\f$ is the recurrent-to-cell weight matrix,\n * \\f$b_c\\f$ is the cell bias,\n * \\f$W_{xo}\\f$ is the input-to-output weight matrix,\n * \\f$W_{ho}\\f$ is the recurrent-to-output weight matrix,\n * \\f$W_{co}\\f$ is the cell-to-output weight matrix,\n * \\f$b_o\\f$ is the output gate bias,\n * \\f$W_{proj}\\f$ is the projection weight matrix,\n * \\f$b_{proj}\\f$ is the projection bias,\n * \\f$t_{cell}\\f$ is the threshold for clipping the cell state, and\n * \\f$t_{proj}\\f$ is the threshold for clipping the projected output.\n * \\f$\\odot\\f$ is the\n   <a href=\"https://en.wikipedia.org/wiki/Hadamard_product_(matrices)\">\n   Hadamard product</a> that takes two matrices and produces another\n   matrix, each element of which is the product of the corresponding\n   elements of the input matrices.\n\n Since API level 29 LSTM supports layer normalization.\n In case layer normalization is used, the inputs to internal activation\n functions (sigmoid and \\f$g\\f$) are normalized, rescaled and recentered\n following an approach from section 3.1 from\n https://arxiv.org/pdf/1607.06450.pdf\n\n The operation has the following independently optional inputs:\n * The cell-to-input weights (\\f$W_{ci}\\f$), cell-to-forget weights\n   (\\f$W_{cf}\\f$) and cell-to-output weights (\\f$W_{co}\\f$) either all\n   have values or neither of them have values (i.e., all set to null). If\n   they have values, the peephole optimization is used.\n * The input-to-input weights (\\f$W_{xi}\\f$), recurrent-to-input weights\n   (\\f$W_{hi}\\f$) and input gate bias (\\f$b_i\\f$) either all have values,\n   or none of them have values. If they have no values, coupling of input\n   and forget gates (CIFG) is used, in which case the input gate\n   (\\f$i_t\\f$) is calculated using the following equation instead.\n   \\f{eqnarray*}{\n   i_t = 1 - f_t\n   \\f}\n   In case peephole optimization is used and CIFG is not used\n   cell-to-input (\\f$W_{ci}\\f$) weights must be present. Otherwise, the\n   cell-to-input weights must have no value.\n * The projection weights (\\f$W_{proj}\\f$) is required only for the\n   recurrent projection layer, and should otherwise have no value.\n * The projection bias (\\f$b_{proj}\\f$) may (but not required to) have a\n   value if the recurrent projection layer exists, and should otherwise\n   have no value.\n * (API level 29 or later) The four layer normalization weights either all have\n   values or none of them have values. Additionally, if CIFG is used,\n   input layer normalization weights tensor is omitted and the other layer\n   normalization weights either all have values or none of them have\n   values. Layer normalization is used when the values of all the layer\n   normalization weights are present.\n\n References:\n\n The default non-peephole non-CIFG implementation is based on:\n <http://www.bioinf.jku.at/publications/older/2604.pdf>\n S. Hochreiter and J. Schmidhuber. \"Long Short-Term Memory\". Neural\n Computation, 9(8):1735-1780, 1997.\n\n The peephole implementation and projection layer is based on:\n https://research.google.com/pubs/archive/43905.pdf\n Hasim Sak, Andrew Senior, and Francoise Beaufays. \"Long short-term memory\n recurrent neural network architectures for large scale acoustic\n modeling.\" INTERSPEECH, 2014.\n (However, the concept of peephole optimization was introduced in work\n prior to this paper.)\n\n The coupling of input and forget gate (CIFG) is based on:\n http://arxiv.org/pdf/1503.04069.pdf\n Greff et al. \"LSTM: A Search Space Odyssey\"\n\n The layer normalization is based on:\n https://arxiv.org/pdf/1607.06450.pdf\n Jimmy Ba et al. \"Layer Normalization\"\n\n Supported tensor {@link OperandCode}:\n * {@link ANEURALNETWORKS_TENSOR_FLOAT16} (since API level 29)\n * {@link ANEURALNETWORKS_TENSOR_FLOAT32}\n\n All input and output tensors must be of the same type.\n\n Inputs:\n * 0: The input (\\f$x_t\\f$).\n      A 2-D tensor of shape [batch_size, input_size], where “batch_size”\n      corresponds to the batching dimension, and “input_size” is the size\n      of the input.\n * 1: The input-to-input weights (\\f$W_{xi}\\f$). Optional.\n      A 2-D tensor of shape [num_units, input_size], where “num_units”\n      corresponds to the number of cell units.\n * 2: The input-to-forget weights (\\f$W_{xf}\\f$).\n      A 2-D tensor of shape [num_units, input_size].\n * 3: The input-to-cell weights (\\f$W_{xc}\\f$).\n      A 2-D tensor of shape [num_units, input_size].\n * 4: The input-to-output weights (\\f$W_{xo}\\f$).\n      A 2-D tensor of shape [num_units, input_size].\n * 5: The recurrent-to-input weights (\\f$W_{hi}\\f$). Optional.\n      A 2-D tensor of shape [num_units, output_size], where “output_size”\n      corresponds to either the number of cell units (i.e., “num_units”),\n      or the second dimension of the “projection_weights”, if defined.\n * 6: The recurrent-to-forget weights (\\f$W_{hf}\\f$).\n      A 2-D tensor of shape [num_units, output_size].\n * 7: The recurrent-to-cell weights (\\f$W_{hc}\\f$).\n      A 2-D tensor of shape [num_units, output_size].\n * 8: The recurrent-to-output weights (\\f$W_{ho}\\f$).\n      A 2-D tensor of shape [num_units, output_size].\n * 9: The cell-to-input weights (\\f$W_{ci}\\f$). Optional.\n      A 1-D tensor of shape [num_units].\n * 10:The cell-to-forget weights (\\f$W_{cf}\\f$). Optional.\n      A 1-D tensor of shape [num_units].\n * 11:The cell-to-output weights (\\f$W_{co}\\f$). Optional.\n      A 1-D tensor of shape [num_units].\n * 12:The input gate bias (\\f$b_i\\f$). Optional.\n      A 1-D tensor of shape [num_units].\n * 13:The forget gate bias (\\f$b_f\\f$).\n      A 1-D tensor of shape [num_units].\n * 14:The cell bias (\\f$b_c\\f$).\n      A 1-D tensor of shape [num_units].\n * 15:The output gate bias (\\f$b_o\\f$).\n      A 1-D tensor of shape [num_units].\n * 16:The projection weights (\\f$W_{proj}\\f$). Optional.\n      A 2-D tensor of shape [output_size, num_units].\n * 17:The projection bias (\\f$b_{proj}\\f$). Optional.\n      A 1-D tensor of shape [output_size].\n * 18:The output state (in) (\\f$h_{t-1}\\f$).\n      A 2-D tensor of shape [batch_size, output_size].\n * 19:The cell state (in) (\\f$C_{t-1}\\f$).\n      A 2-D tensor of shape [batch_size, num_units].\n * 20:The activation function (\\f$g\\f$).\n      A value indicating the activation function:\n      <ul>\n      <li>0: None;\n      <li>1: Relu;\n      <li>3: Relu6;\n      <li>4: Tanh;\n      <li>6: Sigmoid.\n      </ul>\n * 21:The clipping threshold (\\f$t_{cell}\\f$) for the cell state, such\n      that values are bound within [-cell_clip, cell_clip]. If set to 0.0\n      then clipping is disabled.\n      Until API level 29 this scalar must be of type {@link\n      ANEURALNETWORKS_FLOAT32}. Since API level 29, if all the input\n      tensors have type {@link ANEURALNETWORKS_TENSOR_FLOAT32}, this\n      scalar must be of the type {@link ANEURALNETWORKS_FLOAT32},\n      otherwise if all the input tensors have the type {@link\n      ANEURALNETWORKS_TENSOR_FLOAT16}, this scalar must be of type {@link\n      ANEURALNETWORKS_FLOAT16}.\n * 22:The clipping threshold (\\f$t_{proj}\\f$) for the output from the\n      projection layer, such that values are bound within\n      [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.\n      Until API level 29 this scalar must be of type {@link\n      ANEURALNETWORKS_FLOAT32}. Since API level 29, if all the input\n      tensors have type {@link ANEURALNETWORKS_TENSOR_FLOAT32}, this\n      scalar must be of the type {@link ANEURALNETWORKS_FLOAT32},\n      otherwise if all the input tensors have the type {@link\n      ANEURALNETWORKS_TENSOR_FLOAT16}, this scalar must be of type {@link\n      ANEURALNETWORKS_FLOAT16}.\n Since API level 29 there are additional inputs to this op:\n * 23:The input layer normalization weights.\n      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs\n      to activation at input gate.\n * 24:The forget layer normalization weights.\n      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs\n      to activation at forget gate.\n * 25:The cell layer normalization weights.\n      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs\n      to activation at cell gate.\n * 26:The output layer normalization weights.\n      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs\n      to activation at output gate.\n\n Outputs:\n * 0: The scratch buffer.\n      A 2-D tensor of shape [batch_size, num_units * 3] with CIFG, or\n      [batch_size, num_units * 4] without CIFG.\n * 1: The output state (out) (\\f$h_t\\f$).\n      A 2-D tensor of shape [batch_size, output_size].\n * 2: The cell state (out) (\\f$C_t\\f$).\n      A 2-D tensor of shape [batch_size, num_units].\n * 3: The output (\\f$o_t\\f$).\n      A 2-D tensor of shape [batch_size, output_size]. This is effectively\n      the same as the current “output state (out)” value.\n\n Available since API level 27."]
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[INFO] [stdout] 722 | ...on and projection layer is based on:\n https://research.google.com/pubs/archive/43905.pdf\n Hasim Sak, Andrew Senior, and Franco...
[INFO] [stdout]     |                                           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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[INFO] [stdout] 722 |     #[doc = " Performs a single time step in a Long Short-Term Memory (LSTM) layer\n\n The LSTM operation is described by the following equations.\n\n \\f{eqnarray*}{\n i_t =& \\sigma(W_{xi}x_t+W_{hi}h_{t-1}+W_{ci}C_{t-1}+b_i) & \\\\\n f_t =& \\sigma(W_{xf}x_t+W_{hf}h_{t-1}+W_{cf}C_{t-1}+b_f) & \\\\\n C_t =& clip(f_t \\odot C_{t-1} + i_t \\odot\n        g(W_{xc}x_t+W_{hc}h_{t-1}+b_c),\\ t_{cell}) & \\\\\n o_t =& \\sigma(W_{xo}x_t+W_{ho}h_{t-1}+W_{co}C_t+b_o) & \\\\\n      & & \\\\\n      & clip(W_{proj}(o_t \\odot g(C_t))+b_{proj},\\ t_{proj})\n      & if\\ there\\ is\\ a\\ projection; \\\\\n h_t =& & \\\\\n      & o_t \\odot g(C_t) & otherwise. \\\\\n \\f}\n Where:\n * \\f$x_t\\f$ is the input,\n * \\f$i_t\\f$ is the input gate,\n * \\f$f_t\\f$ is the forget gate,\n * \\f$C_t\\f$ is the cell state,\n * \\f$o_t\\f$ is the output,\n * \\f$h_t\\f$ is the output state,\n * \\f$\\sigma\\f$ is the logistic sigmoid function,\n * \\f$g\\f$ is the cell input and cell output activation function, usually\n   \\f$tahn\\f$,\n * \\f$W_{xi}\\f$ is the input-to-input weight matrix,\n * \\f$W_{hi}\\f$ is the recurrent to input weight matrix,\n * \\f$W_{ci}\\f$ is the cell-to-input weight matrix,\n * \\f$b_i\\f$ is the input gate bias,\n * \\f$W_{xf}\\f$ is the input-to-forget weight matrix,\n * \\f$W_{hf}\\f$ is the recurrent-to-forget weight matrix,\n * \\f$W_{cf}\\f$ is the cell-to-forget weight matrix,\n * \\f$b_f\\f$ is the forget gate bias,\n * \\f$W_{xc}\\f$ is the input-to-cell weight matrix,\n * \\f$W_{hc}\\f$ is the recurrent-to-cell weight matrix,\n * \\f$b_c\\f$ is the cell bias,\n * \\f$W_{xo}\\f$ is the input-to-output weight matrix,\n * \\f$W_{ho}\\f$ is the recurrent-to-output weight matrix,\n * \\f$W_{co}\\f$ is the cell-to-output weight matrix,\n * \\f$b_o\\f$ is the output gate bias,\n * \\f$W_{proj}\\f$ is the projection weight matrix,\n * \\f$b_{proj}\\f$ is the projection bias,\n * \\f$t_{cell}\\f$ is the threshold for clipping the cell state, and\n * \\f$t_{proj}\\f$ is the threshold for clipping the projected output.\n * \\f$\\odot\\f$ is the\n   <a href=\"https://en.wikipedia.org/wiki/Hadamard_product_(matrices)\">\n   Hadamard product</a> that takes two matrices and produces another\n   matrix, each element of which is the product of the corresponding\n   elements of the input matrices.\n\n Since API level 29 LSTM supports layer normalization.\n In case layer normalization is used, the inputs to internal activation\n functions (sigmoid and \\f$g\\f$) are normalized, rescaled and recentered\n following an approach from section 3.1 from\n https://arxiv.org/pdf/1607.06450.pdf\n\n The operation has the following independently optional inputs:\n * The cell-to-input weights (\\f$W_{ci}\\f$), cell-to-forget weights\n   (\\f$W_{cf}\\f$) and cell-to-output weights (\\f$W_{co}\\f$) either all\n   have values or neither of them have values (i.e., all set to null). If\n   they have values, the peephole optimization is used.\n * The input-to-input weights (\\f$W_{xi}\\f$), recurrent-to-input weights\n   (\\f$W_{hi}\\f$) and input gate bias (\\f$b_i\\f$) either all have values,\n   or none of them have values. If they have no values, coupling of input\n   and forget gates (CIFG) is used, in which case the input gate\n   (\\f$i_t\\f$) is calculated using the following equation instead.\n   \\f{eqnarray*}{\n   i_t = 1 - f_t\n   \\f}\n   In case peephole optimization is used and CIFG is not used\n   cell-to-input (\\f$W_{ci}\\f$) weights must be present. Otherwise, the\n   cell-to-input weights must have no value.\n * The projection weights (\\f$W_{proj}\\f$) is required only for the\n   recurrent projection layer, and should otherwise have no value.\n * The projection bias (\\f$b_{proj}\\f$) may (but not required to) have a\n   value if the recurrent projection layer exists, and should otherwise\n   have no value.\n * (API level 29 or later) The four layer normalization weights either all have\n   values or none of them have values. Additionally, if CIFG is used,\n   input layer normalization weights tensor is omitted and the other layer\n   normalization weights either all have values or none of them have\n   values. Layer normalization is used when the values of all the layer\n   normalization weights are present.\n\n References:\n\n The default non-peephole non-CIFG implementation is based on:\n http://www.bioinf.jku.at/publications/older/2604.pdf\n S. Hochreiter and J. Schmidhuber. \"Long Short-Term Memory\". Neural\n Computation, 9(8):1735-1780, 1997.\n\n The peephole implementation and projection layer is based on:\n <https://research.google.com/pubs/archive/43905.pdf>\n Hasim Sak, Andrew Senior, and Francoise Beaufays. \"Long short-term memory\n recurrent neural network architectures for large scale acoustic\n modeling.\" INTERSPEECH, 2014.\n (However, the concept of peephole optimization was introduced in work\n prior to this paper.)\n\n The coupling of input and forget gate (CIFG) is based on:\n http://arxiv.org/pdf/1503.04069.pdf\n Greff et al. \"LSTM: A Search Space Odyssey\"\n\n The layer normalization is based on:\n https://arxiv.org/pdf/1607.06450.pdf\n Jimmy Ba et al. \"Layer Normalization\"\n\n Supported tensor {@link OperandCode}:\n * {@link ANEURALNETWORKS_TENSOR_FLOAT16} (since API level 29)\n * {@link ANEURALNETWORKS_TENSOR_FLOAT32}\n\n All input and output tensors must be of the same type.\n\n Inputs:\n * 0: The input (\\f$x_t\\f$).\n      A 2-D tensor of shape [batch_size, input_size], where “batch_size”\n      corresponds to the batching dimension, and “input_size” is the size\n      of the input.\n * 1: The input-to-input weights (\\f$W_{xi}\\f$). Optional.\n      A 2-D tensor of shape [num_units, input_size], where “num_units”\n      corresponds to the number of cell units.\n * 2: The input-to-forget weights (\\f$W_{xf}\\f$).\n      A 2-D tensor of shape [num_units, input_size].\n * 3: The input-to-cell weights (\\f$W_{xc}\\f$).\n      A 2-D tensor of shape [num_units, input_size].\n * 4: The input-to-output weights (\\f$W_{xo}\\f$).\n      A 2-D tensor of shape [num_units, input_size].\n * 5: The recurrent-to-input weights (\\f$W_{hi}\\f$). Optional.\n      A 2-D tensor of shape [num_units, output_size], where “output_size”\n      corresponds to either the number of cell units (i.e., “num_units”),\n      or the second dimension of the “projection_weights”, if defined.\n * 6: The recurrent-to-forget weights (\\f$W_{hf}\\f$).\n      A 2-D tensor of shape [num_units, output_size].\n * 7: The recurrent-to-cell weights (\\f$W_{hc}\\f$).\n      A 2-D tensor of shape [num_units, output_size].\n * 8: The recurrent-to-output weights (\\f$W_{ho}\\f$).\n      A 2-D tensor of shape [num_units, output_size].\n * 9: The cell-to-input weights (\\f$W_{ci}\\f$). Optional.\n      A 1-D tensor of shape [num_units].\n * 10:The cell-to-forget weights (\\f$W_{cf}\\f$). Optional.\n      A 1-D tensor of shape [num_units].\n * 11:The cell-to-output weights (\\f$W_{co}\\f$). Optional.\n      A 1-D tensor of shape [num_units].\n * 12:The input gate bias (\\f$b_i\\f$). Optional.\n      A 1-D tensor of shape [num_units].\n * 13:The forget gate bias (\\f$b_f\\f$).\n      A 1-D tensor of shape [num_units].\n * 14:The cell bias (\\f$b_c\\f$).\n      A 1-D tensor of shape [num_units].\n * 15:The output gate bias (\\f$b_o\\f$).\n      A 1-D tensor of shape [num_units].\n * 16:The projection weights (\\f$W_{proj}\\f$). Optional.\n      A 2-D tensor of shape [output_size, num_units].\n * 17:The projection bias (\\f$b_{proj}\\f$). Optional.\n      A 1-D tensor of shape [output_size].\n * 18:The output state (in) (\\f$h_{t-1}\\f$).\n      A 2-D tensor of shape [batch_size, output_size].\n * 19:The cell state (in) (\\f$C_{t-1}\\f$).\n      A 2-D tensor of shape [batch_size, num_units].\n * 20:The activation function (\\f$g\\f$).\n      A value indicating the activation function:\n      <ul>\n      <li>0: None;\n      <li>1: Relu;\n      <li>3: Relu6;\n      <li>4: Tanh;\n      <li>6: Sigmoid.\n      </ul>\n * 21:The clipping threshold (\\f$t_{cell}\\f$) for the cell state, such\n      that values are bound within [-cell_clip, cell_clip]. If set to 0.0\n      then clipping is disabled.\n      Until API level 29 this scalar must be of type {@link\n      ANEURALNETWORKS_FLOAT32}. Since API level 29, if all the input\n      tensors have type {@link ANEURALNETWORKS_TENSOR_FLOAT32}, this\n      scalar must be of the type {@link ANEURALNETWORKS_FLOAT32},\n      otherwise if all the input tensors have the type {@link\n      ANEURALNETWORKS_TENSOR_FLOAT16}, this scalar must be of type {@link\n      ANEURALNETWORKS_FLOAT16}.\n * 22:The clipping threshold (\\f$t_{proj}\\f$) for the output from the\n      projection layer, such that values are bound within\n      [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.\n      Until API level 29 this scalar must be of type {@link\n      ANEURALNETWORKS_FLOAT32}. Since API level 29, if all the input\n      tensors have type {@link ANEURALNETWORKS_TENSOR_FLOAT32}, this\n      scalar must be of the type {@link ANEURALNETWORKS_FLOAT32},\n      otherwise if all the input tensors have the type {@link\n      ANEURALNETWORKS_TENSOR_FLOAT16}, this scalar must be of type {@link\n      ANEURALNETWORKS_FLOAT16}.\n Since API level 29 there are additional inputs to this op:\n * 23:The input layer normalization weights.\n      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs\n      to activation at input gate.\n * 24:The forget layer normalization weights.\n      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs\n      to activation at forget gate.\n * 25:The cell layer normalization weights.\n      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs\n      to activation at cell gate.\n * 26:The output layer normalization weights.\n      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs\n      to activation at output gate.\n\n Outputs:\n * 0: The scratch buffer.\n      A 2-D tensor of shape [batch_size, num_units * 3] with CIFG, or\n      [batch_size, num_units * 4] without CIFG.\n * 1: The output state (out) (\\f$h_t\\f$).\n      A 2-D tensor of shape [batch_size, output_size].\n * 2: The cell state (out) (\\f$C_t\\f$).\n      A 2-D tensor of shape [batch_size, num_units].\n * 3: The output (\\f$o_t\\f$).\n      A 2-D tensor of shape [batch_size, output_size]. This is effectively\n      the same as the current “output state (out)” value.\n\n Available since API level 27."]
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[INFO] [stdout] 722 | ...f input and forget gate (CIFG) is based on:\n http://arxiv.org/pdf/1503.04069.pdf\n Greff et al. \"LSTM: A Search Space Odyssey\...
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[INFO] [stdout] 722 |     #[doc = " Performs a single time step in a Long Short-Term Memory (LSTM) layer\n\n The LSTM operation is described by the following equations.\n\n \\f{eqnarray*}{\n i_t =& \\sigma(W_{xi}x_t+W_{hi}h_{t-1}+W_{ci}C_{t-1}+b_i) & \\\\\n f_t =& \\sigma(W_{xf}x_t+W_{hf}h_{t-1}+W_{cf}C_{t-1}+b_f) & \\\\\n C_t =& clip(f_t \\odot C_{t-1} + i_t \\odot\n        g(W_{xc}x_t+W_{hc}h_{t-1}+b_c),\\ t_{cell}) & \\\\\n o_t =& \\sigma(W_{xo}x_t+W_{ho}h_{t-1}+W_{co}C_t+b_o) & \\\\\n      & & \\\\\n      & clip(W_{proj}(o_t \\odot g(C_t))+b_{proj},\\ t_{proj})\n      & if\\ there\\ is\\ a\\ projection; \\\\\n h_t =& & \\\\\n      & o_t \\odot g(C_t) & otherwise. \\\\\n \\f}\n Where:\n * \\f$x_t\\f$ is the input,\n * \\f$i_t\\f$ is the input gate,\n * \\f$f_t\\f$ is the forget gate,\n * \\f$C_t\\f$ is the cell state,\n * \\f$o_t\\f$ is the output,\n * \\f$h_t\\f$ is the output state,\n * \\f$\\sigma\\f$ is the logistic sigmoid function,\n * \\f$g\\f$ is the cell input and cell output activation function, usually\n   \\f$tahn\\f$,\n * \\f$W_{xi}\\f$ is the input-to-input weight matrix,\n * \\f$W_{hi}\\f$ is the recurrent to input weight matrix,\n * \\f$W_{ci}\\f$ is the cell-to-input weight matrix,\n * \\f$b_i\\f$ is the input gate bias,\n * \\f$W_{xf}\\f$ is the input-to-forget weight matrix,\n * \\f$W_{hf}\\f$ is the recurrent-to-forget weight matrix,\n * \\f$W_{cf}\\f$ is the cell-to-forget weight matrix,\n * \\f$b_f\\f$ is the forget gate bias,\n * \\f$W_{xc}\\f$ is the input-to-cell weight matrix,\n * \\f$W_{hc}\\f$ is the recurrent-to-cell weight matrix,\n * \\f$b_c\\f$ is the cell bias,\n * \\f$W_{xo}\\f$ is the input-to-output weight matrix,\n * \\f$W_{ho}\\f$ is the recurrent-to-output weight matrix,\n * \\f$W_{co}\\f$ is the cell-to-output weight matrix,\n * \\f$b_o\\f$ is the output gate bias,\n * \\f$W_{proj}\\f$ is the projection weight matrix,\n * \\f$b_{proj}\\f$ is the projection bias,\n * \\f$t_{cell}\\f$ is the threshold for clipping the cell state, and\n * \\f$t_{proj}\\f$ is the threshold for clipping the projected output.\n * \\f$\\odot\\f$ is the\n   <a href=\"https://en.wikipedia.org/wiki/Hadamard_product_(matrices)\">\n   Hadamard product</a> that takes two matrices and produces another\n   matrix, each element of which is the product of the corresponding\n   elements of the input matrices.\n\n Since API level 29 LSTM supports layer normalization.\n In case layer normalization is used, the inputs to internal activation\n functions (sigmoid and \\f$g\\f$) are normalized, rescaled and recentered\n following an approach from section 3.1 from\n https://arxiv.org/pdf/1607.06450.pdf\n\n The operation has the following independently optional inputs:\n * The cell-to-input weights (\\f$W_{ci}\\f$), cell-to-forget weights\n   (\\f$W_{cf}\\f$) and cell-to-output weights (\\f$W_{co}\\f$) either all\n   have values or neither of them have values (i.e., all set to null). If\n   they have values, the peephole optimization is used.\n * The input-to-input weights (\\f$W_{xi}\\f$), recurrent-to-input weights\n   (\\f$W_{hi}\\f$) and input gate bias (\\f$b_i\\f$) either all have values,\n   or none of them have values. If they have no values, coupling of input\n   and forget gates (CIFG) is used, in which case the input gate\n   (\\f$i_t\\f$) is calculated using the following equation instead.\n   \\f{eqnarray*}{\n   i_t = 1 - f_t\n   \\f}\n   In case peephole optimization is used and CIFG is not used\n   cell-to-input (\\f$W_{ci}\\f$) weights must be present. Otherwise, the\n   cell-to-input weights must have no value.\n * The projection weights (\\f$W_{proj}\\f$) is required only for the\n   recurrent projection layer, and should otherwise have no value.\n * The projection bias (\\f$b_{proj}\\f$) may (but not required to) have a\n   value if the recurrent projection layer exists, and should otherwise\n   have no value.\n * (API level 29 or later) The four layer normalization weights either all have\n   values or none of them have values. Additionally, if CIFG is used,\n   input layer normalization weights tensor is omitted and the other layer\n   normalization weights either all have values or none of them have\n   values. Layer normalization is used when the values of all the layer\n   normalization weights are present.\n\n References:\n\n The default non-peephole non-CIFG implementation is based on:\n http://www.bioinf.jku.at/publications/older/2604.pdf\n S. Hochreiter and J. Schmidhuber. \"Long Short-Term Memory\". Neural\n Computation, 9(8):1735-1780, 1997.\n\n The peephole implementation and projection layer is based on:\n https://research.google.com/pubs/archive/43905.pdf\n Hasim Sak, Andrew Senior, and Francoise Beaufays. \"Long short-term memory\n recurrent neural network architectures for large scale acoustic\n modeling.\" INTERSPEECH, 2014.\n (However, the concept of peephole optimization was introduced in work\n prior to this paper.)\n\n The coupling of input and forget gate (CIFG) is based on:\n <http://arxiv.org/pdf/1503.04069.pdf>\n Greff et al. \"LSTM: A Search Space Odyssey\"\n\n The layer normalization is based on:\n https://arxiv.org/pdf/1607.06450.pdf\n Jimmy Ba et al. \"Layer Normalization\"\n\n Supported tensor {@link OperandCode}:\n * {@link ANEURALNETWORKS_TENSOR_FLOAT16} (since API level 29)\n * {@link ANEURALNETWORKS_TENSOR_FLOAT32}\n\n All input and output tensors must be of the same type.\n\n Inputs:\n * 0: The input (\\f$x_t\\f$).\n      A 2-D tensor of shape [batch_size, input_size], where “batch_size”\n      corresponds to the batching dimension, and “input_size” is the size\n      of the input.\n * 1: The input-to-input weights (\\f$W_{xi}\\f$). Optional.\n      A 2-D tensor of shape [num_units, input_size], where “num_units”\n      corresponds to the number of cell units.\n * 2: The input-to-forget weights (\\f$W_{xf}\\f$).\n      A 2-D tensor of shape [num_units, input_size].\n * 3: The input-to-cell weights (\\f$W_{xc}\\f$).\n      A 2-D tensor of shape [num_units, input_size].\n * 4: The input-to-output weights (\\f$W_{xo}\\f$).\n      A 2-D tensor of shape [num_units, input_size].\n * 5: The recurrent-to-input weights (\\f$W_{hi}\\f$). Optional.\n      A 2-D tensor of shape [num_units, output_size], where “output_size”\n      corresponds to either the number of cell units (i.e., “num_units”),\n      or the second dimension of the “projection_weights”, if defined.\n * 6: The recurrent-to-forget weights (\\f$W_{hf}\\f$).\n      A 2-D tensor of shape [num_units, output_size].\n * 7: The recurrent-to-cell weights (\\f$W_{hc}\\f$).\n      A 2-D tensor of shape [num_units, output_size].\n * 8: The recurrent-to-output weights (\\f$W_{ho}\\f$).\n      A 2-D tensor of shape [num_units, output_size].\n * 9: The cell-to-input weights (\\f$W_{ci}\\f$). Optional.\n      A 1-D tensor of shape [num_units].\n * 10:The cell-to-forget weights (\\f$W_{cf}\\f$). Optional.\n      A 1-D tensor of shape [num_units].\n * 11:The cell-to-output weights (\\f$W_{co}\\f$). Optional.\n      A 1-D tensor of shape [num_units].\n * 12:The input gate bias (\\f$b_i\\f$). Optional.\n      A 1-D tensor of shape [num_units].\n * 13:The forget gate bias (\\f$b_f\\f$).\n      A 1-D tensor of shape [num_units].\n * 14:The cell bias (\\f$b_c\\f$).\n      A 1-D tensor of shape [num_units].\n * 15:The output gate bias (\\f$b_o\\f$).\n      A 1-D tensor of shape [num_units].\n * 16:The projection weights (\\f$W_{proj}\\f$). Optional.\n      A 2-D tensor of shape [output_size, num_units].\n * 17:The projection bias (\\f$b_{proj}\\f$). Optional.\n      A 1-D tensor of shape [output_size].\n * 18:The output state (in) (\\f$h_{t-1}\\f$).\n      A 2-D tensor of shape [batch_size, output_size].\n * 19:The cell state (in) (\\f$C_{t-1}\\f$).\n      A 2-D tensor of shape [batch_size, num_units].\n * 20:The activation function (\\f$g\\f$).\n      A value indicating the activation function:\n      <ul>\n      <li>0: None;\n      <li>1: Relu;\n      <li>3: Relu6;\n      <li>4: Tanh;\n      <li>6: Sigmoid.\n      </ul>\n * 21:The clipping threshold (\\f$t_{cell}\\f$) for the cell state, such\n      that values are bound within [-cell_clip, cell_clip]. If set to 0.0\n      then clipping is disabled.\n      Until API level 29 this scalar must be of type {@link\n      ANEURALNETWORKS_FLOAT32}. Since API level 29, if all the input\n      tensors have type {@link ANEURALNETWORKS_TENSOR_FLOAT32}, this\n      scalar must be of the type {@link ANEURALNETWORKS_FLOAT32},\n      otherwise if all the input tensors have the type {@link\n      ANEURALNETWORKS_TENSOR_FLOAT16}, this scalar must be of type {@link\n      ANEURALNETWORKS_FLOAT16}.\n * 22:The clipping threshold (\\f$t_{proj}\\f$) for the output from the\n      projection layer, such that values are bound within\n      [-proj_clip, proj_clip]. If set to 0.0 then clipping is disabled.\n      Until API level 29 this scalar must be of type {@link\n      ANEURALNETWORKS_FLOAT32}. Since API level 29, if all the input\n      tensors have type {@link ANEURALNETWORKS_TENSOR_FLOAT32}, this\n      scalar must be of the type {@link ANEURALNETWORKS_FLOAT32},\n      otherwise if all the input tensors have the type {@link\n      ANEURALNETWORKS_TENSOR_FLOAT16}, this scalar must be of type {@link\n      ANEURALNETWORKS_FLOAT16}.\n Since API level 29 there are additional inputs to this op:\n * 23:The input layer normalization weights.\n      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs\n      to activation at input gate.\n * 24:The forget layer normalization weights.\n      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs\n      to activation at forget gate.\n * 25:The cell layer normalization weights.\n      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs\n      to activation at cell gate.\n * 26:The output layer normalization weights.\n      A 1-D tensor of shape [num_units]. Used to rescale normalized inputs\n      to activation at output gate.\n\n Outputs:\n * 0: The scratch buffer.\n      A 2-D tensor of shape [batch_size, num_units * 3] with CIFG, or\n      [batch_size, num_units * 4] without CIFG.\n * 1: The output state (out) (\\f$h_t\\f$).\n      A 2-D tensor of shape [batch_size, output_size].\n * 2: The cell state (out) (\\f$C_t\\f$).\n      A 2-D tensor of shape [batch_size, num_units].\n * 3: The output (\\f$o_t\\f$).\n      A 2-D tensor of shape [batch_size, output_size]. This is effectively\n      the same as the current “output state (out)” value.\n\n Available since API level 27."]
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                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  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[INFO] [stdout]    --> src/neural_networks.rs:722:13
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[INFO] [stdout] 722 | ... = " Performs a single time step in a Long Shor...)” value.\n\n Available since API level 27."]
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[INFO] [stdout]    --> src/neural_networks.rs:744:275
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[INFO] [stdout] 744 | ...s. The implementation is based on:\n\n https://research.google.com/pubs/archive/43813.pdf\n\n P. Nakkiran, R. Alvarez, R. Prabha...
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[INFO] [stdout] 744 |     #[doc = " SVDF op is a kind of stateful layer derived from the notion that a\n densely connected layer that's processing a sequence of input frames can\n be approximated by using a singular value decomposition of each of its\n nodes. The implementation is based on:\n\n <https://research.google.com/pubs/archive/43813.pdf>\n\n P. Nakkiran, R. Alvarez, R. Prabhavalkar, C. Parada.\n “Compressing Deep Neural Networks using a Rank-Constrained Topology”.\n INTERSPEECH, 2015.\n\n It processes the incoming input using a 2-stage filtering mechanism:\n * stage 1 performs filtering on the \"features\" dimension, whose outputs\n   get pushed into a memory of fixed-size memory_size.\n * stage 2 performs filtering on the \"time\" dimension of the memory_size\n   memoized outputs of stage 1.\n\n Specifically, for rank 1, this layer implements the operation:\n\n     memory = push(conv1d(inputs, weights_feature, feature_dim,\n                          \"ANEURALNETWORKS_PADDING_VALID\"));\n     outputs = activation(memory * weights_time + bias);\n\n Where:\n * “weights_feature” is a weights matrix that processes the inputs (by\n   convolving the input with every “feature filter”), and whose outputs\n   get pushed, stacked in order, into the fixed-size “memory” (the oldest\n   entry gets dropped);\n * “weights_time” is a weights matrix that processes the “memory” (by a\n   batched matrix multiplication on the num_units);\n * “bias” is an optional bias vector (added to each output vector in the\n   batch); and\n * “activation” is the function passed as the “fused_activation_function”\n   argument (if not “NONE”).\n\n Each rank adds a dimension to the weights matrices by means of stacking\n the filters.\n\n Supported tensor {@link OperandCode}:\n * {@link ANEURALNETWORKS_TENSOR_FLOAT16} (since API level 29)\n * {@link ANEURALNETWORKS_TENSOR_FLOAT32}\n\n All input tensors must be the same type.\n\n Inputs:\n * 0: input.\n      A 2-D tensor of shape [batch_size, input_size], where “batch_size”\n      corresponds to the batching dimension, and “input_size” is the size\n      of the input.\n * 1: weights_feature.\n      A 2-D tensor of shape [num_units, input_size], where “num_units”\n      corresponds to the number of units.\n * 2: weights_time.\n      A 2-D tensor of shape [num_units, memory_size], where “memory_size”\n      corresponds to the fixed-size of the memory.\n * 3: bias.\n      An optional 1-D tensor of shape [num_units].\n * 4: state (in).\n      A 2-D tensor of shape [batch_size, (memory_size - 1) * num_units * rank].\n * 5: rank.\n      The rank of the SVD approximation.\n * 6: fused_activation_function.\n      An optional {@link FuseCode} value indicating the\n      activation function. If “NONE” is specified then it results in a\n      linear activation.\n\n Outputs:\n * 0: state (out).\n      A 2-D tensor of the same {@link OperandCode} as the inputs, with shape\n      [batch_size, (memory_size - 1) * num_units * rank].\n * 1: output.\n      A 2-D tensor of the same {@link OperandCode} as the inputs, with shape\n      [batch_size, num_units].\n\n Available since API level 27."]
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[INFO] [stdout]    --> src/neural_networks.rs:774:13
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[INFO] [stdout] 774 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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[INFO] [stdout]    --> src/neural_networks.rs:774:13
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[INFO] [stdout] 774 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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[INFO] [stdout]    --> src/neural_networks.rs:776:13
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[INFO] [stdout] 776 | ... = " A recurrent neural network layer that appl...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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[INFO] [stdout]    --> src/neural_networks.rs:834:133
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[INFO] [stdout] 834 | ...8_ASYMM} output tensor is:\n\n     output = max(0, min(255, round(input / scale) + zeroPoint)\n\n The formula for {@link ANEURAL...
[INFO] [stdout]     |                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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[INFO] [stdout]    --> src/neural_networks.rs:834:291
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[INFO] [stdout] 834 | ...NED} output\n tensor is:\n\n     output = max(-128, min(127, round(input / scale) + zeroPoint)\n\n Supported input tensor {@link...
[INFO] [stdout]     |                                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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[INFO] [stdout]    --> src/neural_networks.rs:874:13
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[INFO] [stdout] 874 | ... = " A recurrent neural network specified by an...e chained and state tensors are propagated."]
[INFO] [stdout]     |       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^...^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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[INFO] [stdout]    --> src/neural_networks.rs:888:125
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[INFO] [stdout] 888 | ...\n\n Hard swish activation is introduced in\n https://arxiv.org/pdf/1905.02244.pdf\n\n The output is calculated using the follow...
[INFO] [stdout]     |                                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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[INFO] [stdout] 888 |     #[doc = " Computes hard-swish activation on the input tensor element-wise.\n\n Hard swish activation is introduced in\n <https://arxiv.org/pdf/1905.02244.pdf>\n\n The output is calculated using the following formula:\n\n     h-swish(x) = x * max(0, min(6, (x + 3))) / 6\n\n Supported tensor {@link OperandCode}:\n * {@link ANEURALNETWORKS_TENSOR_FLOAT16}\n * {@link ANEURALNETWORKS_TENSOR_FLOAT32}\n * {@link ANEURALNETWORKS_TENSOR_QUANT8_ASYMM}\n * {@link ANEURALNETWORKS_TENSOR_QUANT8_ASYMM_SIGNED}\n\n Supported tensor rank: from 1.\n\n Inputs:\n * 0: A tensor, specifying the input. May be zero-sized.\n\n Outputs:\n * 0: The output tensor of same shape and type as input0.\n      Scale and zero point of this tensor may be different from the input\n      tensor's parameters.\n\n Available since API level 30."]
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[INFO] [stdout]     --> src/neural_networks.rs:1140:800
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[INFO] [stdout] 1140 | ...rand type in the case of referenced model input operands.\n\n <p>In the following situations, a tensor operand type must be ful...
[INFO] [stdout]      |                                                                  ^^^
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[INFO] [stderr] thread 'rustc' (33) panicked at src/librustdoc/html/markdown.rs:534:22:
[INFO] [stderr] a production-ready version of this should handle the error somehow: LatexError(3, UnknownCommand("f"))
[INFO] [stderr] stack backtrace:
[INFO] [stderr]    0:     0x743a88046d9b - <<std[6281e874092a0dfc]::sys::backtrace::BacktraceLock>::print::DisplayBacktrace as core[37ab4a9f28f6fd13]::fmt::Display>::fmt
[INFO] [stderr]    1:     0x743a8860ef88 - core[37ab4a9f28f6fd13]::fmt::write
[INFO] [stderr]    2:     0x743a8805dc36 - <std[6281e874092a0dfc]::sys::stdio::unix::Stderr as std[6281e874092a0dfc]::io::Write>::write_fmt
[INFO] [stderr]    3:     0x743a8801ce48 - std[6281e874092a0dfc]::panicking::default_hook::{closure#0}
[INFO] [stderr]    4:     0x743a8803a163 - std[6281e874092a0dfc]::panicking::default_hook
[INFO] [stderr]    5:     0x743a8700ff8d - std[6281e874092a0dfc]::panicking::update_hook::<alloc[56313f94ec8c6695]::boxed::Box<rustc_driver_impl[3f098eb6bc26bcd1]::install_ice_hook::{closure#1}>>::{closure#0}
[INFO] [stderr]    6:     0x743a8803a442 - std[6281e874092a0dfc]::panicking::panic_with_hook
[INFO] [stderr]    7:     0x743a8801cf08 - std[6281e874092a0dfc]::panicking::panic_handler::{closure#0}
[INFO] [stderr]    8:     0x743a88011479 - std[6281e874092a0dfc]::sys::backtrace::__rust_end_short_backtrace::<std[6281e874092a0dfc]::panicking::panic_handler::{closure#0}, !>
[INFO] [stderr]    9:     0x743a8801e96d - __rustc[670611b3f56fc7d7]::rust_begin_unwind
[INFO] [stderr]   10:     0x743a84cce58c - core[37ab4a9f28f6fd13]::panicking::panic_fmt
[INFO] [stderr]   11:     0x743a84988b72 - core[37ab4a9f28f6fd13]::result::unwrap_failed
[INFO] [stderr]   12:     0x62f95d75351e - <rustdoc[7f40747ea455e46f]::html::markdown::Math<rustdoc[7f40747ea455e46f]::html::markdown::TableWrapper<core[37ab4a9f28f6fd13]::iter::adapters::map::Map<rustdoc[7f40747ea455e46f]::html::markdown::footnotes::Footnotes<rustdoc[7f40747ea455e46f]::html::markdown::SpannedLinkReplacer<rustdoc[7f40747ea455e46f]::html::markdown::HeadingLinks<pulldown_cmark[baa249b750500f7c]::parse::OffsetIter<<rustdoc[7f40747ea455e46f]::html::markdown::Markdown>::into_iter::{closure#0}>>>>, <rustdoc[7f40747ea455e46f]::html::markdown::Markdown>::into_iter::{closure#1}::{closure#0}>>> as core[37ab4a9f28f6fd13]::iter::traits::iterator::Iterator>::next
[INFO] [stderr]   13:     0x62f95d6e9c16 - <rustdoc[7f40747ea455e46f]::html::markdown::CodeBlocks<rustdoc[7f40747ea455e46f]::html::markdown::Math<rustdoc[7f40747ea455e46f]::html::markdown::TableWrapper<core[37ab4a9f28f6fd13]::iter::adapters::map::Map<rustdoc[7f40747ea455e46f]::html::markdown::footnotes::Footnotes<rustdoc[7f40747ea455e46f]::html::markdown::SpannedLinkReplacer<rustdoc[7f40747ea455e46f]::html::markdown::HeadingLinks<pulldown_cmark[baa249b750500f7c]::parse::OffsetIter<<rustdoc[7f40747ea455e46f]::html::markdown::Markdown>::into_iter::{closure#0}>>>>, <rustdoc[7f40747ea455e46f]::html::markdown::Markdown>::into_iter::{closure#1}::{closure#0}>>>> as core[37ab4a9f28f6fd13]::iter::traits::iterator::Iterator>::next
[INFO] [stderr]   14:     0x62f95d54f493 - <pulldown_cmark[baa249b750500f7c]::html::HtmlWriter<rustdoc[7f40747ea455e46f]::html::markdown::CodeBlocks<rustdoc[7f40747ea455e46f]::html::markdown::Math<rustdoc[7f40747ea455e46f]::html::markdown::TableWrapper<core[37ab4a9f28f6fd13]::iter::adapters::map::Map<rustdoc[7f40747ea455e46f]::html::markdown::footnotes::Footnotes<rustdoc[7f40747ea455e46f]::html::markdown::SpannedLinkReplacer<rustdoc[7f40747ea455e46f]::html::markdown::HeadingLinks<pulldown_cmark[baa249b750500f7c]::parse::OffsetIter<<rustdoc[7f40747ea455e46f]::html::markdown::Markdown>::into_iter::{closure#0}>>>>, <rustdoc[7f40747ea455e46f]::html::markdown::Markdown>::into_iter::{closure#1}::{closure#0}>>>>, pulldown_cmark_escape[cb8658d251f4e39e]::FmtWriter<&mut core[37ab4a9f28f6fd13]::fmt::Formatter>>>::run
[INFO] [stderr]   15:     0x62f95d39eb80 - <rustdoc[7f40747ea455e46f]::html::markdown::Markdown>::write_into::<&mut core[37ab4a9f28f6fd13]::fmt::Formatter>
[INFO] [stderr]   16:     0x62f95d742521 - <core[37ab4a9f28f6fd13]::fmt::builders::FromFn<rustdoc[7f40747ea455e46f]::html::render::render_markdown::{closure#0}> as core[37ab4a9f28f6fd13]::fmt::Display>::fmt
[INFO] [stderr]   17:     0x743a8860ef88 - core[37ab4a9f28f6fd13]::fmt::write
[INFO] [stderr]   18:     0x62f95d7435da - <core[37ab4a9f28f6fd13]::fmt::builders::FromFn<rustdoc[7f40747ea455e46f]::html::render::document_full_inner::{closure#0}> as core[37ab4a9f28f6fd13]::fmt::Display>::fmt
[INFO] [stderr]   19:     0x743a8860ef88 - core[37ab4a9f28f6fd13]::fmt::write
[INFO] [stderr]   20:     0x62f95d7445a5 - <core[37ab4a9f28f6fd13]::fmt::builders::FromFn<rustdoc[7f40747ea455e46f]::html::render::document::{closure#0}> as core[37ab4a9f28f6fd13]::fmt::Display>::fmt
[INFO] [stderr]   21:     0x743a8860ef88 - core[37ab4a9f28f6fd13]::fmt::write
[INFO] [stderr]   22:     0x62f95d74976c - <core[37ab4a9f28f6fd13]::fmt::builders::FromFn<rustdoc[7f40747ea455e46f]::html::render::print_item::item_variants::{closure#0}> as core[37ab4a9f28f6fd13]::fmt::Display>::fmt
[INFO] [stderr]   23:     0x743a8860ef88 - core[37ab4a9f28f6fd13]::fmt::write
[INFO] [stderr]   24:     0x62f95d36303d - <rustdoc[7f40747ea455e46f]::html::render::print_item::DisplayEnum>::render_into::<core[37ab4a9f28f6fd13]::fmt::Formatter>
[INFO] [stderr]   25:     0x62f95d74e3f9 - <core[37ab4a9f28f6fd13]::fmt::builders::FromFn<rustdoc[7f40747ea455e46f]::html::render::print_item::item_enum::{closure#0}> as core[37ab4a9f28f6fd13]::fmt::Display>::fmt
[INFO] [stderr]   26:     0x743a8860ef88 - core[37ab4a9f28f6fd13]::fmt::write
[INFO] [stderr]   27:     0x62f95d43ac6a - rustdoc[7f40747ea455e46f]::html::layout::render::<core[37ab4a9f28f6fd13]::fmt::builders::FromFn<rustdoc[7f40747ea455e46f]::html::render::print_item::print_item::{closure#0}>, core[37ab4a9f28f6fd13]::fmt::builders::FromFn<<rustdoc[7f40747ea455e46f]::html::render::context::Context>::render_item::{closure#1}>>
[INFO] [stderr]   28:     0x62f95d58eb85 - <rustdoc[7f40747ea455e46f]::html::render::context::Context>::render_item
[INFO] [stderr]   29:     0x62f95d729a5e - <rustdoc[7f40747ea455e46f]::html::render::context::Context as rustdoc[7f40747ea455e46f]::formats::renderer::FormatRenderer>::item
[INFO] [stderr]   30:     0x62f95d443adc - rustdoc[7f40747ea455e46f]::formats::renderer::run_format_inner::<rustdoc[7f40747ea455e46f]::html::render::context::Context>
[INFO] [stderr]   31:     0x62f95d443c8f - rustdoc[7f40747ea455e46f]::formats::renderer::run_format_inner::<rustdoc[7f40747ea455e46f]::html::render::context::Context>
[INFO] [stderr]   32:     0x62f95d443c8f - rustdoc[7f40747ea455e46f]::formats::renderer::run_format_inner::<rustdoc[7f40747ea455e46f]::html::render::context::Context>
[INFO] [stderr]   33:     0x62f95d50c39f - rustdoc[7f40747ea455e46f]::main_args::{closure#2}::{closure#0}
[INFO] [stderr]   34:     0x62f95d500100 - rustc_interface[7c235db06cadd779]::interface::run_compiler::<(), rustdoc[7f40747ea455e46f]::main_args::{closure#2}>::{closure#1}
[INFO] [stderr]   35:     0x62f95d439078 - std[6281e874092a0dfc]::sys::backtrace::__rust_begin_short_backtrace::<rustc_interface[7c235db06cadd779]::util::run_in_thread_with_globals<rustc_interface[7c235db06cadd779]::util::run_in_thread_pool_with_globals<rustc_interface[7c235db06cadd779]::interface::run_compiler<(), rustdoc[7f40747ea455e46f]::main_args::{closure#2}>::{closure#1}, ()>::{closure#0}, ()>::{closure#0}::{closure#0}, ()>
[INFO] [stderr]   36:     0x62f95d532df7 - <std[6281e874092a0dfc]::thread::lifecycle::spawn_unchecked<rustc_interface[7c235db06cadd779]::util::run_in_thread_with_globals<rustc_interface[7c235db06cadd779]::util::run_in_thread_pool_with_globals<rustc_interface[7c235db06cadd779]::interface::run_compiler<(), rustdoc[7f40747ea455e46f]::main_args::{closure#2}>::{closure#1}, ()>::{closure#0}, ()>::{closure#0}::{closure#0}, ()>::{closure#1} as core[37ab4a9f28f6fd13]::ops::function::FnOnce<()>>::call_once::{shim:vtable#0}
[INFO] [stderr]   37:     0x743a8981dbac - <std[6281e874092a0dfc]::sys::thread::unix::Thread>::new::thread_start
[INFO] [stderr]   38:     0x743a8328aaa4 - <unknown>
[INFO] [stderr]   39:     0x743a83317a64 - clone
[INFO] [stderr]   40:                0x0 - <unknown>
[INFO] [stderr] 
[INFO] [stderr] error: the compiler unexpectedly panicked. this is a bug.
[INFO] [stderr] 
[INFO] [stderr] note: we would appreciate a bug report: https://github.com/rust-lang/rust/issues/new?labels=C-bug%2C+I-ICE%2C+T-rustdoc&template=ice.md
[INFO] [stderr] 
[INFO] [stderr] note: please make sure that you have updated to the latest nightly
[INFO] [stderr] 
[INFO] [stderr] warning: the ICE couldn't be written to `/opt/rustwide/workdir/rustc-ice-2026-02-09T21_14_28-32.txt`: Read-only file system (os error 30)
[INFO] [stderr] 
[INFO] [stderr] note: rustc 1.95.0-nightly (a394c9cd9 2026-01-31) running on x86_64-unknown-linux-gnu
[INFO] [stderr] 
[INFO] [stderr] note: compiler flags: --crate-type lib
[INFO] [stderr] 
[INFO] [stderr] note: some of the compiler flags provided by cargo are hidden
[INFO] [stderr] 
[INFO] [stderr] query stack during panic:
[INFO] [stderr] end of query stack
[INFO] [stderr] error: could not document `nnapi-sys`
[INFO] running `Command { std: "docker" "inspect" "6d7dafc2146bb12114bee71de02e644a7c26a14a1d1f0e8225e5093ddd8b302f", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "rm" "-f" "6d7dafc2146bb12114bee71de02e644a7c26a14a1d1f0e8225e5093ddd8b302f", kill_on_drop: false }`
[INFO] [stdout] 6d7dafc2146bb12114bee71de02e644a7c26a14a1d1f0e8225e5093ddd8b302f
