[INFO] fetching crate tract-nnef 0.12.1...
[INFO] testing tract-nnef-0.12.1 against beta-2021-01-01 for beta-1.50-1
[INFO] extracting crate tract-nnef 0.12.1 into /workspace/builds/worker-8/source
[INFO] validating manifest of crates.io crate tract-nnef 0.12.1 on toolchain beta-2021-01-01
[INFO] running `Command { std: "/workspace/cargo-home/bin/cargo" "+beta-2021-01-01" "read-manifest" "--manifest-path" "Cargo.toml", kill_on_drop: false }`
[INFO] started tweaking crates.io crate tract-nnef 0.12.1
[INFO] finished tweaking crates.io crate tract-nnef 0.12.1
[INFO] tweaked toml for crates.io crate tract-nnef 0.12.1 written to /workspace/builds/worker-8/source/Cargo.toml
[INFO] running `Command { std: "/workspace/cargo-home/bin/cargo" "+beta-2021-01-01" "generate-lockfile" "--manifest-path" "Cargo.toml" "-Zno-index-update", kill_on_drop: false }`
[INFO] [stderr]     Blocking waiting for file lock on package cache
[INFO] running `Command { std: "/workspace/cargo-home/bin/cargo" "+beta-2021-01-01" "fetch" "--locked" "--manifest-path" "Cargo.toml", kill_on_drop: false }`
[INFO] [stderr]     Blocking waiting for file lock on package cache
[INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-8/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-8/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" "rustops/crates-build-env@sha256:b8eeb62f26c39b23691079a6cb6de528d8e88b4d71a8f6b1d30f8ba7d9c16de9" "/opt/rustwide/cargo-home/bin/cargo" "+beta-2021-01-01" "metadata" "--no-deps" "--format-version=1", kill_on_drop: false }`
[INFO] [stdout] 5e50cd77f4a32ea3f6d25777395d58296c3afa0e227f0e581d03459924d98c73
[INFO] [stderr] WARNING: Your kernel does not support swap limit capabilities or the cgroup is not mounted. Memory limited without swap.
[INFO] running `Command { std: "docker" "start" "-a" "5e50cd77f4a32ea3f6d25777395d58296c3afa0e227f0e581d03459924d98c73", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "inspect" "5e50cd77f4a32ea3f6d25777395d58296c3afa0e227f0e581d03459924d98c73", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "rm" "-f" "5e50cd77f4a32ea3f6d25777395d58296c3afa0e227f0e581d03459924d98c73", kill_on_drop: false }`
[INFO] [stdout] 5e50cd77f4a32ea3f6d25777395d58296c3afa0e227f0e581d03459924d98c73
[INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-8/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-8/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=warn" "-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" "rustops/crates-build-env@sha256:b8eeb62f26c39b23691079a6cb6de528d8e88b4d71a8f6b1d30f8ba7d9c16de9" "/opt/rustwide/cargo-home/bin/cargo" "+beta-2021-01-01" "build" "--frozen" "--message-format=json", kill_on_drop: false }`
[INFO] [stdout] f2f1acf3febde1333b1c52212db439d5746f5224b611045243bd2959a5c067ce
[INFO] [stderr] WARNING: Your kernel does not support swap limit capabilities or the cgroup is not mounted. Memory limited without swap.
[INFO] running `Command { std: "docker" "start" "-a" "f2f1acf3febde1333b1c52212db439d5746f5224b611045243bd2959a5c067ce", kill_on_drop: false }`
[INFO] [stderr]    Compiling ndarray v0.13.0
[INFO] [stderr]    Compiling downcast-rs v1.2.0
[INFO] [stderr]    Compiling num-traits v0.2.14
[INFO] [stderr]    Compiling num-integer v0.1.44
[INFO] [stderr]    Compiling num-bigint v0.3.1
[INFO] [stderr]    Compiling itertools v0.8.2
[INFO] [stderr]    Compiling proc-quote-impl v0.3.2
[INFO] [stderr]    Compiling xattr v0.2.2
[INFO] [stderr]    Compiling derive-new v0.5.8
[INFO] [stderr]    Compiling kstring v1.0.0
[INFO] [stderr]    Compiling tar v0.4.30
[INFO] [stderr]    Compiling proc-quote v0.3.2
[INFO] [stderr]    Compiling liquid-derive v0.21.0
[INFO] [stderr]    Compiling num-complex v0.2.4
[INFO] [stderr]    Compiling chrono v0.4.19
[INFO] [stderr]    Compiling liquid-core v0.21.2
[INFO] [stderr]    Compiling enum-ordinalize v3.1.8
[INFO] [stderr]    Compiling educe v0.4.11
[INFO] [stderr]    Compiling liquid-lib v0.21.1
[INFO] [stderr]    Compiling liquid v0.21.4
[INFO] [stderr]    Compiling tract-data v0.12.1
[INFO] [stderr]    Compiling tract-linalg v0.12.1
[INFO] [stderr]    Compiling tract-core v0.12.1
[INFO] [stderr]    Compiling tract-nnef v0.12.1 (/opt/rustwide/workdir)
[INFO] [stderr]     Finished dev [unoptimized + debuginfo] target(s) in 2m 13s
[INFO] running `Command { std: "docker" "inspect" "f2f1acf3febde1333b1c52212db439d5746f5224b611045243bd2959a5c067ce", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "rm" "-f" "f2f1acf3febde1333b1c52212db439d5746f5224b611045243bd2959a5c067ce", kill_on_drop: false }`
[INFO] [stdout] f2f1acf3febde1333b1c52212db439d5746f5224b611045243bd2959a5c067ce
[INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-8/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-8/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=warn" "-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" "rustops/crates-build-env@sha256:b8eeb62f26c39b23691079a6cb6de528d8e88b4d71a8f6b1d30f8ba7d9c16de9" "/opt/rustwide/cargo-home/bin/cargo" "+beta-2021-01-01" "test" "--frozen" "--no-run" "--message-format=json", kill_on_drop: false }`
[INFO] [stdout] c503e1b6c2e806208a1cd8447a1f573eddc6c54be18201985df298354336bd9e
[INFO] [stderr] WARNING: Your kernel does not support swap limit capabilities or the cgroup is not mounted. Memory limited without swap.
[INFO] running `Command { std: "docker" "start" "-a" "c503e1b6c2e806208a1cd8447a1f573eddc6c54be18201985df298354336bd9e", kill_on_drop: false }`
[INFO] [stderr]    Compiling tract-nnef v0.12.1 (/opt/rustwide/workdir)
[INFO] [stderr]     Finished test [unoptimized + debuginfo] target(s) in 12.69s
[INFO] running `Command { std: "docker" "inspect" "c503e1b6c2e806208a1cd8447a1f573eddc6c54be18201985df298354336bd9e", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "rm" "-f" "c503e1b6c2e806208a1cd8447a1f573eddc6c54be18201985df298354336bd9e", kill_on_drop: false }`
[INFO] [stdout] c503e1b6c2e806208a1cd8447a1f573eddc6c54be18201985df298354336bd9e
[INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-8/target:/opt/rustwide/target:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-8/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=warn" "-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" "rustops/crates-build-env@sha256:b8eeb62f26c39b23691079a6cb6de528d8e88b4d71a8f6b1d30f8ba7d9c16de9" "/opt/rustwide/cargo-home/bin/cargo" "+beta-2021-01-01" "test" "--frozen", kill_on_drop: false }`
[INFO] [stderr] WARNING: Your kernel does not support swap limit capabilities or the cgroup is not mounted. Memory limited without swap.
[INFO] [stdout] 98cf90747fe86230a038bf11b04a65b6ddeb1e46d18903cc047757f74e64f09c
[INFO] running `Command { std: "docker" "start" "-a" "98cf90747fe86230a038bf11b04a65b6ddeb1e46d18903cc047757f74e64f09c", kill_on_drop: false }`
[INFO] [stderr]     Finished test [unoptimized + debuginfo] target(s) in 0.13s
[INFO] [stderr]      Running /opt/rustwide/target/debug/deps/tract_nnef-af889ee0a33771f9
[INFO] [stdout] 
[INFO] [stdout] running 28 tests
[INFO] [stdout] test ast::parse::test::test_document ... ok
[INFO] [stdout] test ast::parse::test::test_arguments ... ok
[INFO] [stdout] test ast::parse::test::test_fragment_decl_fizz ... ok
[INFO] [stdout] test ast::parse::test::test_fragment_decl_external ... ok
[INFO] [stdout] test ast::parse::test::test_freeze ... ignored
[INFO] [stdout] test ast::parse::test::test_fragment_conv ... ok
[INFO] [stdout] test ast::parse::test::test_body ... ok
[INFO] [stdout] test ast::parse::test::test_fragment_reshape ... ok
[INFO] [stdout] test ast::parse::test::test_graph_def ... ok
[INFO] [stdout] test ast::parse::test::test_batch_normalization ... ok
[INFO] [stdout] test ast::parse::test::test_fragment_decl_logarithmic_quantize ... ok
[INFO] [stdout] test ast::parse::test::test_comprehenion ... ok
[INFO] [stdout] test ast::parse::test::test_identifier ... ok
[INFO] [stdout] test ast::parse::test::test_invocation ... ok
[INFO] [stdout] test ast::parse::test::test_lvalue ... ok
[INFO] [stdout] test ast::parse::test::test_fragments ... ok
[INFO] [stdout] test ast::parse::test::test_spaced ... ok
[INFO] [stdout] test ast::parse::test::test_version ... ok
[INFO] [stdout] test ast::parse::test::test_spacing ... ok
[INFO] [stdout] test tensors::test::header_is_128_bytes ... ok
[INFO] [stdout] test ast::parse::test::test_string ... ok
[INFO] [stdout] test ast::parse::test::test_numeric ... ok
[INFO] [stdout] test ast::parse::test::test_fragment_local_response_normalization ... ok
[INFO] [stdout] test ast::parse::test::test_type_spec ... ok
[INFO] [stdout] test ast::parse::test::test_avg_roi_align ... ok
[INFO] [stdout] test ast::parse::test::test_rvalue ... ok
[INFO] [stdout] test ast::parse::test::test_min_max_linear_quantize ... ok
[INFO] [stdout] test ast::parse::test::test_assignment ... ok
[INFO] [stdout] 
[INFO] [stdout] test result: ok. 27 passed; 0 failed; 1 ignored; 0 measured; 0 filtered out; finished in 0.38s
[INFO] [stdout] 
[INFO] [stderr]      Running /opt/rustwide/target/debug/deps/parse-2878902881759918
[INFO] [stdout] 
[INFO] [stdout] running 4 tests
[INFO] [stdout] test parse_stdlib ... ok
[INFO] [stdout] test parse_alexnet ... ok
[INFO] [stdout] test parse_dump_parse_alexnet ... ok
[INFO] [stdout] test parse_dump_parse_stdlib ... FAILED
[INFO] [stdout] 
[INFO] [stdout] failures:
[INFO] [stdout] 
[INFO] [stdout] ---- parse_dump_parse_stdlib stdout ----
[INFO] [stdout] fragment abs(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment add(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     y: tensor<scalar>
[INFO] [stdout] ) -> (z: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment add_n(
[INFO] [stdout]     x: tensor<scalar>[]
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = (x[0] + add_n(x[1:])) if (length_of(x) > 0) else constant(shape = [1], value = [0.0]);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment all_reduce(
[INFO] [stdout]     input: tensor<logical>,
[INFO] [stdout]     axes: integer[]
[INFO] [stdout] ) -> (output: tensor<logical>)
[INFO] [stdout] ;
[INFO] [stdout] fragment and(
[INFO] [stdout]     x: tensor<logical>,
[INFO] [stdout]     y: tensor<logical>
[INFO] [stdout] ) -> (z: tensor<logical>)
[INFO] [stdout] ;
[INFO] [stdout] fragment any_reduce(
[INFO] [stdout]     input: tensor<logical>,
[INFO] [stdout]     axes: integer[]
[INFO] [stdout] ) -> (output: tensor<logical>)
[INFO] [stdout] ;
[INFO] [stdout] fragment area_downsample(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     factor: integer[]
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   dims = (2 + length_of(factor));
[INFO] [stdout]   output = box(input, size = ([1, 1] + factor), stride = ([1, 1] + factor), padding = ([(0, 0)] * dims), normalize = true);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment argmax_pool(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     size: integer[],
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     padding: (integer, integer)[] = [],
[INFO] [stdout]     stride: integer[] = [],
[INFO] [stdout]     dilation: integer[] = []
[INFO] [stdout] ) -> (index: tensor<integer>)
[INFO] [stdout] ;
[INFO] [stdout] fragment argmax_reduce(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     axes: integer[]
[INFO] [stdout] ) -> (output: tensor<integer>)
[INFO] [stdout] ;
[INFO] [stdout] fragment argmin_reduce(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     axes: integer[]
[INFO] [stdout] ) -> (output: tensor<integer>)
[INFO] [stdout] ;
[INFO] [stdout] fragment avg_pool(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     size: integer[],
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     padding: (integer, integer)[] = [],
[INFO] [stdout]     stride: integer[] = [],
[INFO] [stdout]     dilation: integer[] = []
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   output = box(input, size = size, border = border, padding = padding, stride = stride, dilation = dilation, normalize = true);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment avg_roi_align(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     rois: tensor<scalar>,
[INFO] [stdout]     batch_index: tensor<integer>,
[INFO] [stdout]     output_size: integer[],
[INFO] [stdout]     sampling_rate: integer[],
[INFO] [stdout]     resize_method: string = "symmetric"
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   size = [ fori in range_of(output_size) yield (output_size[i] * sampling_rate[i])];
[INFO] [stdout]   resized = roi_resample(input, rois, batch_index, output_size = size, method = resize_method);
[INFO] [stdout]   output = avg_pool(resized, size = sampling_rate, stride = sampling_rate);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment avg_roi_pool(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     rois: tensor<scalar>,
[INFO] [stdout]     batch_index: tensor<integer>,
[INFO] [stdout]     output_size: integer[]
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment batch_normalization(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     mean: tensor<scalar>,
[INFO] [stdout]     variance: tensor<scalar>,
[INFO] [stdout]     offset: tensor<scalar>,
[INFO] [stdout]     scale: tensor<scalar>,
[INFO] [stdout]     epsilon: scalar
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   output = (offset + ((scale * (input - mean)) / sqrt((variance + epsilon))));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment box(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     size: integer[],
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     padding: (integer, integer)[] = [],
[INFO] [stdout]     stride: integer[] = [],
[INFO] [stdout]     dilation: integer[] = [],
[INFO] [stdout]     normalize: logical = false
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment ceil(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment clamp(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     a: tensor<scalar>,
[INFO] [stdout]     b: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = max(min(x, b), a);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment concat<?>(
[INFO] [stdout]     values: tensor<?>[],
[INFO] [stdout]     axis: integer
[INFO] [stdout] ) -> (value: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment constant<?=scalar>(
[INFO] [stdout]     shape: integer[],
[INFO] [stdout]     value: ?[]
[INFO] [stdout] ) -> (output: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment conv(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     filter: tensor<scalar>,
[INFO] [stdout]     bias: tensor<scalar> = 0.0,
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     padding: (integer, integer)[] = [],
[INFO] [stdout]     stride: integer[] = [],
[INFO] [stdout]     dilation: integer[] = [],
[INFO] [stdout]     groups: integer = 1
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment copy<?>(
[INFO] [stdout]     x: tensor<?>
[INFO] [stdout] ) -> (y: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment copy_n<?>(
[INFO] [stdout]     x: tensor<?>,
[INFO] [stdout]     times: integer
[INFO] [stdout] ) -> (y: tensor<?>[])
[INFO] [stdout] {
[INFO] [stdout]   y = ([x] * times);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment cos(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment debox(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     size: integer[],
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     padding: (integer, integer)[] = [],
[INFO] [stdout]     stride: integer[] = [],
[INFO] [stdout]     dilation: integer[] = [],
[INFO] [stdout]     output_shape: integer[] = [],
[INFO] [stdout]     normalize: logical = false
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment deconv(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     filter: tensor<scalar>,
[INFO] [stdout]     bias: tensor<scalar> = 0.0,
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     padding: (integer, integer)[] = [],
[INFO] [stdout]     stride: integer[] = [],
[INFO] [stdout]     dilation: integer[] = [],
[INFO] [stdout]     output_shape: integer[] = [],
[INFO] [stdout]     groups: integer = 1
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment desample(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     index: tensor<integer>,
[INFO] [stdout]     size: integer[],
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     padding: (integer, integer)[] = [],
[INFO] [stdout]     stride: integer[] = [],
[INFO] [stdout]     dilation: integer[] = [],
[INFO] [stdout]     output_shape: integer[] = []
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment div(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     y: tensor<scalar>
[INFO] [stdout] ) -> (z: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment elu(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = select((x < 0.0), (exp(x) - 1.0), x);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment eq(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     y: tensor<scalar>
[INFO] [stdout] ) -> (z: tensor<logical>)
[INFO] [stdout] ;
[INFO] [stdout] fragment exp(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment external<?=scalar>(
[INFO] [stdout]     shape: integer[]
[INFO] [stdout] ) -> (output: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment floor(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment ge(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     y: tensor<scalar>
[INFO] [stdout] ) -> (z: tensor<logical>)
[INFO] [stdout] ;
[INFO] [stdout] fragment gt(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     y: tensor<scalar>
[INFO] [stdout] ) -> (z: tensor<logical>)
[INFO] [stdout] ;
[INFO] [stdout] fragment l1_normalization(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     axes: integer[],
[INFO] [stdout]     bias: scalar = 0.0,
[INFO] [stdout]     epsilon: scalar = 0.0
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   sigma = sum_reduce(abs(input), axes = axes);
[INFO] [stdout]   output = (input / max((sigma + bias), epsilon));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment l2_normalization(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     axes: integer[],
[INFO] [stdout]     bias: scalar = 0.0,
[INFO] [stdout]     epsilon: scalar = 0.0
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   sigma = sqrt(sum_reduce(sqr(input), axes = axes));
[INFO] [stdout]   output = (input / max((sigma + bias), epsilon));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment le(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     y: tensor<scalar>
[INFO] [stdout] ) -> (z: tensor<logical>)
[INFO] [stdout] ;
[INFO] [stdout] fragment leaky_relu(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     alpha: scalar
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = prelu(x, alpha = alpha);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment linear(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     filter: tensor<scalar>,
[INFO] [stdout]     bias: tensor<scalar> = 0.0
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   output = (matmul(input, filter, transposeB = true) + bias);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment linear_quantize(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     min: tensor<scalar>,
[INFO] [stdout]     max: tensor<scalar>,
[INFO] [stdout]     bits: integer
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = min_max_linear_quantize(x, min = min, max = max, bits = bits, signed = false, symmetric = false);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment local_contrast_normalization(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     size: integer[],
[INFO] [stdout]     bias: scalar = 0.0,
[INFO] [stdout]     epsilon: scalar = 0.0
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   centered = local_mean_normalization(input, size = size);
[INFO] [stdout]   output = local_variance_normalization(centered, size = size, bias = bias, epsilon = epsilon);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment local_mean_normalization(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     size: integer[]
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   mean = box(input, size = size, normalize = true);
[INFO] [stdout]   output = sub(input, mean);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment local_response_normalization(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     size: integer[],
[INFO] [stdout]     alpha: scalar = 1.0,
[INFO] [stdout]     beta: scalar = 0.5,
[INFO] [stdout]     bias: scalar = 1.0
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   sigma = (bias + (alpha * box(sqr(input), size = size, normalize = true)));
[INFO] [stdout]   output = (input / (sigma ^ beta));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment local_variance_normalization(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     size: integer[],
[INFO] [stdout]     bias: scalar = 0.0,
[INFO] [stdout]     epsilon: scalar = 0.0
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   sigma = sqrt(box(sqr(input), size = size, normalize = true));
[INFO] [stdout]   output = (input / max((sigma + bias), epsilon));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment log(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment log2(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = (log(x) / log(2.0));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment logarithmic_quantize(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     max: tensor<scalar>,
[INFO] [stdout]     bits: integer
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   m = ceil(log2(max));
[INFO] [stdout]   r = scalar(((2 ^ bits) - 1));
[INFO] [stdout]   q = round(clamp(log2(abs(x)), (m - r), m));
[INFO] [stdout]   y = (sign(x) * (2.0 ^ q));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment lt(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     y: tensor<scalar>
[INFO] [stdout] ) -> (z: tensor<logical>)
[INFO] [stdout] ;
[INFO] [stdout] fragment matmul(
[INFO] [stdout]     A: tensor<scalar>,
[INFO] [stdout]     B: tensor<scalar>,
[INFO] [stdout]     transposeA: logical = false,
[INFO] [stdout]     transposeB: logical = false
[INFO] [stdout] ) -> (C: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment max(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     y: tensor<scalar>
[INFO] [stdout] ) -> (z: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   z = select((x > y), x, y);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment max_pool(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     size: integer[],
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     padding: (integer, integer)[] = [],
[INFO] [stdout]     stride: integer[] = [],
[INFO] [stdout]     dilation: integer[] = []
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   ( output, index ) = max_pool_with_index(input, size = size, border = border, padding = padding, stride = stride, dilation = dilation);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment max_pool_with_index(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     size: integer[],
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     padding: (integer, integer)[] = [],
[INFO] [stdout]     stride: integer[] = [],
[INFO] [stdout]     dilation: integer[] = []
[INFO] [stdout] ) -> (output: tensor<scalar>, index: tensor<integer>)
[INFO] [stdout] {
[INFO] [stdout]   index = argmax_pool(input, size = size, border = border, padding = padding, stride = stride, dilation = dilation);
[INFO] [stdout]   output = sample(input, index, size = size, border = border, padding = padding, stride = stride, dilation = dilation);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment max_reduce(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     axes: integer[]
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment max_roi_align(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     rois: tensor<scalar>,
[INFO] [stdout]     batch_index: tensor<integer>,
[INFO] [stdout]     output_size: integer[],
[INFO] [stdout]     sampling_rate: integer[],
[INFO] [stdout]     resize_method: string = "symmetric"
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   size = [ fori in range_of(output_size) yield (output_size[i] * sampling_rate[i])];
[INFO] [stdout]   resized = roi_resample(input, rois, batch_index, output_size = size, method = resize_method);
[INFO] [stdout]   output = max_pool(resized, size = sampling_rate, stride = sampling_rate);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment max_roi_pool(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     rois: tensor<scalar>,
[INFO] [stdout]     batch_index: tensor<integer>,
[INFO] [stdout]     output_size: integer[]
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment mean_reduce(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     axes: integer[]
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   output = sum_reduce(input, axes = axes, normalize = true);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment min(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     y: tensor<scalar>
[INFO] [stdout] ) -> (z: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   z = select((x < y), x, y);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment min_max_linear_quantize(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     min: tensor<scalar>,
[INFO] [stdout]     max: tensor<scalar>,
[INFO] [stdout]     bits: integer,
[INFO] [stdout]     signed: logical,
[INFO] [stdout]     symmetric: logical
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   r = scalar((((2 ^ bits) - 1) - integer((signed && symmetric))));
[INFO] [stdout]   z = clamp(x, min, max);
[INFO] [stdout]   p = scalar(((2 ^ (bits - 1)) - integer(symmetric)) if signed else 0);
[INFO] [stdout]   q = (round((((z - min) / (max - min)) * r)) - p);
[INFO] [stdout]   y = ((((q + p) / r) * (max - min)) + min);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment min_reduce(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     axes: integer[]
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment moments(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     axes: integer[]
[INFO] [stdout] ) -> (mean: tensor<scalar>, variance: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   mean = mean_reduce(input, axes = axes);
[INFO] [stdout]   variance = mean_reduce(sqr((input - mean)), axes = axes);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment mul(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     y: tensor<scalar>
[INFO] [stdout] ) -> (z: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment multilinear_upsample(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     factor: integer[],
[INFO] [stdout]     method: string = "symmetric",
[INFO] [stdout]     border: string = "replicate"
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment ne(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     y: tensor<scalar>
[INFO] [stdout] ) -> (z: tensor<logical>)
[INFO] [stdout] ;
[INFO] [stdout] fragment nearest_downsample(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     factor: integer[]
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   dims = (2 + length_of(factor));
[INFO] [stdout]   output = box(input, size = ([1] * dims), stride = ([1, 1] + factor), padding = ([(0, 0)] * dims));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment nearest_upsample(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     factor: integer[]
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   dims = (2 + length_of(factor));
[INFO] [stdout]   output = debox(input, size = ([1, 1] + factor), stride = ([1, 1] + factor), padding = ([(0, 0)] * dims));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment neg(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment not(
[INFO] [stdout]     x: tensor<logical>
[INFO] [stdout] ) -> (y: tensor<logical>)
[INFO] [stdout] ;
[INFO] [stdout] fragment or(
[INFO] [stdout]     x: tensor<logical>,
[INFO] [stdout]     y: tensor<logical>
[INFO] [stdout] ) -> (z: tensor<logical>)
[INFO] [stdout] ;
[INFO] [stdout] fragment pad(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     padding: (integer, integer)[],
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     value: scalar = 0.0
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment pow(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     y: tensor<scalar>
[INFO] [stdout] ) -> (z: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment prelu(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     alpha: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = select((x < 0.0), (alpha * x), x);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment rcp(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment relu(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = max(x, 0.0);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment reshape<?>(
[INFO] [stdout]     input: tensor<?>,
[INFO] [stdout]     shape: integer[],
[INFO] [stdout]     axis_start: integer = 0,
[INFO] [stdout]     axis_count: integer = -1
[INFO] [stdout] ) -> (output: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment rms_pool(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     size: integer[],
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     padding: (integer, integer)[] = [],
[INFO] [stdout]     stride: integer[] = [],
[INFO] [stdout]     dilation: integer[] = []
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   output = sqrt(avg_pool(sqr(input), size = size, border = border, padding = padding, stride = stride, dilation = dilation));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment roi_resample(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     rois: tensor<scalar>,
[INFO] [stdout]     batch_index: tensor<integer>,
[INFO] [stdout]     output_size: integer[],
[INFO] [stdout]     method: string = "symmetric"
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment round(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment rsqr(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = (x ^ -2.0);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment rsqrt(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = (x ^ -0.5);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment sample(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     index: tensor<integer>,
[INFO] [stdout]     size: integer[],
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     padding: (integer, integer)[] = [],
[INFO] [stdout]     stride: integer[] = [],
[INFO] [stdout]     dilation: integer[] = []
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment select<?>(
[INFO] [stdout]     condition: tensor<logical>,
[INFO] [stdout]     true_value: tensor<?>,
[INFO] [stdout]     false_value: tensor<?>
[INFO] [stdout] ) -> (output: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment separable_conv(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     plane_filter: tensor<scalar>,
[INFO] [stdout]     point_filter: tensor<scalar>,
[INFO] [stdout]     bias: tensor<scalar> = 0.0,
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     padding: (integer, integer)[] = [],
[INFO] [stdout]     stride: integer[] = [],
[INFO] [stdout]     dilation: integer[] = [],
[INFO] [stdout]     groups: integer = 1
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   filtered = conv(input, plane_filter, border = border, padding = padding, stride = stride, dilation = dilation, groups = 0);
[INFO] [stdout]   output = conv(filtered, point_filter, bias, groups = groups);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment separable_deconv(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     plane_filter: tensor<scalar>,
[INFO] [stdout]     point_filter: tensor<scalar>,
[INFO] [stdout]     bias: tensor<scalar> = 0.0,
[INFO] [stdout]     border: string = "constant",
[INFO] [stdout]     padding: (integer, integer)[] = [],
[INFO] [stdout]     stride: integer[] = [],
[INFO] [stdout]     dilation: integer[] = [],
[INFO] [stdout]     output_shape: integer[] = [],
[INFO] [stdout]     groups: integer = 1
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   filtered = deconv(input, point_filter, groups = groups);
[INFO] [stdout]   output = deconv(filtered, plane_filter, bias, border = border, padding = padding, stride = stride, dilation = dilation, output_shape = output_shape, groups = 0);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment sigmoid(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = (1.0 / (1.0 + exp(-x)));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment sign(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment sin(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment slice<?>(
[INFO] [stdout]     input: tensor<?>,
[INFO] [stdout]     axes: integer[],
[INFO] [stdout]     begin: integer[],
[INFO] [stdout]     end: integer[]
[INFO] [stdout] ) -> (output: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment softabs(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     epsilon: scalar
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = sqrt((sqr(x) + epsilon));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment softmax(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     axes: integer[] = [1]
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   m = max_reduce(x, axes = axes);
[INFO] [stdout]   e = exp((x - m));
[INFO] [stdout]   y = (e / sum_reduce(e, axes = axes));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment softplus(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = log((exp(x) + 1.0));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment split<?>(
[INFO] [stdout]     value: tensor<?>,
[INFO] [stdout]     axis: integer,
[INFO] [stdout]     ratios: integer[]
[INFO] [stdout] ) -> (values: tensor<?>[])
[INFO] [stdout] ;
[INFO] [stdout] fragment sqr(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = (x ^ 2.0);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment sqrt(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = (x ^ 0.5);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment squeeze<?>(
[INFO] [stdout]     input: tensor<?>,
[INFO] [stdout]     axes: integer[]
[INFO] [stdout] ) -> (output: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment stack<?>(
[INFO] [stdout]     values: tensor<?>[],
[INFO] [stdout]     axis: integer
[INFO] [stdout] ) -> (value: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment sub(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     y: tensor<scalar>
[INFO] [stdout] ) -> (z: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment sum_reduce(
[INFO] [stdout]     input: tensor<scalar>,
[INFO] [stdout]     axes: integer[],
[INFO] [stdout]     normalize: logical = false
[INFO] [stdout] ) -> (output: tensor<scalar>)
[INFO] [stdout] ;
[INFO] [stdout] fragment tanh(
[INFO] [stdout]     x: tensor<scalar>
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   y = ((exp(x) - exp(-x)) / (exp(x) + exp(-x)));
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] fragment tile<?>(
[INFO] [stdout]     input: tensor<?>,
[INFO] [stdout]     repeats: integer[]
[INFO] [stdout] ) -> (output: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment transpose<?>(
[INFO] [stdout]     input: tensor<?>,
[INFO] [stdout]     axes: integer[]
[INFO] [stdout] ) -> (output: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment unsqueeze<?>(
[INFO] [stdout]     input: tensor<?>,
[INFO] [stdout]     axes: integer[]
[INFO] [stdout] ) -> (output: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment unstack<?>(
[INFO] [stdout]     value: tensor<?>,
[INFO] [stdout]     axis: integer
[INFO] [stdout] ) -> (values: tensor<?>[])
[INFO] [stdout] ;
[INFO] [stdout] fragment update<?>(
[INFO] [stdout]     variable: tensor<?>,
[INFO] [stdout]     value: tensor<?>
[INFO] [stdout] ) -> (result: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment variable<?=scalar>(
[INFO] [stdout]     shape: integer[],
[INFO] [stdout]     label: string
[INFO] [stdout] ) -> (output: tensor<?>)
[INFO] [stdout] ;
[INFO] [stdout] fragment zero_point_linear_quantize(
[INFO] [stdout]     x: tensor<scalar>,
[INFO] [stdout]     zero_point: integer,
[INFO] [stdout]     scale: scalar,
[INFO] [stdout]     bits: integer,
[INFO] [stdout]     signed: logical,
[INFO] [stdout]     symmetric: logical
[INFO] [stdout] ) -> (y: tensor<scalar>)
[INFO] [stdout] {
[INFO] [stdout]   z = (round((x / scale)) + scalar(zero_point));
[INFO] [stdout]   r = scalar(((2 ^ (bits - 1)) - 1) if signed else ((2 ^ bits) - 1));
[INFO] [stdout]   q = clamp(z, 0.0 if !signed else -r if symmetric else -(r - 1.0), r);
[INFO] [stdout]   y = ((q - scalar(zero_point)) * scale);
[INFO] [stdout] }
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] thread 'parse_dump_parse_stdlib' panicked at 'assertion failed: `(left == right)`
[INFO] [stdout]   left: `FragmentDef { decl: FragmentDecl { id: "external", generic_decl: Some(Some(Scalar)), parameters: [Parameter { id: "shape", spec: Array(Single(Integer)), lit: None }], results: [Result_ { id: "output", spec: Tensor(Any) }] }, body: None }`,
[INFO] [stdout]  right: `FragmentDef { decl: FragmentDecl { id: "abs", generic_decl: None, parameters: [Parameter { id: "x", spec: Tensor(Scalar), lit: None }], results: [Result_ { id: "y", spec: Tensor(Scalar) }] }, body: None }`', tests/parse.rs:42:9
[INFO] [stdout] stack backtrace:
[INFO] [stdout]    0:     0x563d595c17c7 - std::backtrace_rs::backtrace::libunwind::trace::hcd6e187547b8deec
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/../../backtrace/src/backtrace/libunwind.rs:90:5
[INFO] [stdout]    1:     0x563d595c17c7 - std::backtrace_rs::backtrace::trace_unsynchronized::hde10036eb783fbc7
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/../../backtrace/src/backtrace/mod.rs:66:5
[INFO] [stdout]    2:     0x563d595c17c7 - std::sys_common::backtrace::_print_fmt::h63987b8f86dfc82a
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/sys_common/backtrace.rs:67:5
[INFO] [stdout]    3:     0x563d595c17c7 - <std::sys_common::backtrace::_print::DisplayBacktrace as core::fmt::Display>::fmt::hc33f3ac4cc9c4196
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/sys_common/backtrace.rs:46:22
[INFO] [stdout]    4:     0x563d595e197c - core::fmt::write::hfdcdeb08fb2b3afa
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/core/src/fmt/mod.rs:1078:17
[INFO] [stdout]    5:     0x563d595bdc42 - std::io::Write::write_fmt::h28c53dc51251a293
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/io/mod.rs:1519:15
[INFO] [stdout]    6:     0x563d595c3a75 - std::sys_common::backtrace::_print::hf179508b01f66878
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/sys_common/backtrace.rs:49:5
[INFO] [stdout]    7:     0x563d595c3a75 - std::sys_common::backtrace::print::ha97d11adb39266a6
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/sys_common/backtrace.rs:36:9
[INFO] [stdout]    8:     0x563d595c3a75 - std::panicking::default_hook::{{closure}}::h8da9985a98bd1582
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/panicking.rs:208:50
[INFO] [stdout]    9:     0x563d595c3602 - std::panicking::default_hook::hbc0ee792993c2ef2
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/panicking.rs:222:9
[INFO] [stdout]   10:     0x563d595c4211 - std::panicking::rust_panic_with_hook::h9fb9cda33a10f084
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/panicking.rs:591:17
[INFO] [stdout]   11:     0x563d595c3d57 - std::panicking::begin_panic_handler::{{closure}}::hf3e83396e085962e
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/panicking.rs:497:13
[INFO] [stdout]   12:     0x563d595c1c8c - std::sys_common::backtrace::__rust_end_short_backtrace::hac151ac4c1e3252d
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/sys_common/backtrace.rs:141:18
[INFO] [stdout]   13:     0x563d595c3cb9 - rust_begin_unwind
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/panicking.rs:493:5
[INFO] [stdout]   14:     0x563d595e0331 - core::panicking::panic_fmt::hf6d8a92b065b8f97
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/core/src/panicking.rs:92:14
[INFO] [stdout]   15:     0x563d594af0f6 - parse::parse_dump_parse_stdlib::hbc0953947f3e75ee
[INFO] [stdout]                                at /opt/rustwide/workdir/tests/parse.rs:42:9
[INFO] [stdout]   16:     0x563d594ae88a - parse::parse_dump_parse_stdlib::{{closure}}::h4d98147ff0a8f56f
[INFO] [stdout]                                at /opt/rustwide/workdir/tests/parse.rs:30:1
[INFO] [stdout]   17:     0x563d594b141e - core::ops::function::FnOnce::call_once::h164088099aacfe61
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/core/src/ops/function.rs:227:5
[INFO] [stdout]   18:     0x563d594db483 - core::ops::function::FnOnce::call_once::ha61d5393ae51ae22
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/core/src/ops/function.rs:227:5
[INFO] [stdout]   19:     0x563d594db483 - test::__rust_begin_short_backtrace::h4a8691b5281c1f3b
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/test/src/lib.rs:516:5
[INFO] [stdout]   20:     0x563d594d9d76 - <alloc::boxed::Box<F,A> as core::ops::function::FnOnce<Args>>::call_once::hd25ba61494055ad3
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/alloc/src/boxed.rs:1328:9
[INFO] [stdout]   21:     0x563d594d9d76 - <std::panic::AssertUnwindSafe<F> as core::ops::function::FnOnce<()>>::call_once::h052fde7b846767ba
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/panic.rs:322:9
[INFO] [stdout]   22:     0x563d594d9d76 - std::panicking::try::do_call::h04571a1da6838ba1
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/panicking.rs:379:40
[INFO] [stdout]   23:     0x563d594d9d76 - std::panicking::try::h758f090614125cbe
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/panicking.rs:343:19
[INFO] [stdout]   24:     0x563d594d9d76 - std::panic::catch_unwind::h0c48513d5a021d3c
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/panic.rs:396:14
[INFO] [stdout]   25:     0x563d594d9d76 - test::run_test_in_process::hee75babaaac3822f
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/test/src/lib.rs:538:18
[INFO] [stdout]   26:     0x563d594d9d76 - test::run_test::run_test_inner::{{closure}}::h2920dea75d7f0c1e
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/test/src/lib.rs:449:39
[INFO] [stdout]   27:     0x563d594b2086 - std::sys_common::backtrace::__rust_begin_short_backtrace::ha23dff608830db13
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/sys_common/backtrace.rs:125:18
[INFO] [stdout]   28:     0x563d594b6e1d - std::thread::Builder::spawn_unchecked::{{closure}}::{{closure}}::hacce322dead3a799
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/thread/mod.rs:474:17
[INFO] [stdout]   29:     0x563d594b6e1d - <std::panic::AssertUnwindSafe<F> as core::ops::function::FnOnce<()>>::call_once::h4f0bc9c26ead0a27
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/panic.rs:322:9
[INFO] [stdout]   30:     0x563d594b6e1d - std::panicking::try::do_call::h1b9f282fb0c383b3
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/panicking.rs:379:40
[INFO] [stdout]   31:     0x563d594b6e1d - std::panicking::try::hed1ebed51b133ee4
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/panicking.rs:343:19
[INFO] [stdout]   32:     0x563d594b6e1d - std::panic::catch_unwind::h072a2b19fd39a474
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/panic.rs:396:14
[INFO] [stdout]   33:     0x563d594b6e1d - std::thread::Builder::spawn_unchecked::{{closure}}::hb02c6b2d3ff18bc2
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/thread/mod.rs:473:30
[INFO] [stdout]   34:     0x563d594b6e1d - core::ops::function::FnOnce::call_once{{vtable.shim}}::hb512c5d27b4adb83
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/core/src/ops/function.rs:227:5
[INFO] [stdout]   35:     0x563d595c9d6a - <alloc::boxed::Box<F,A> as core::ops::function::FnOnce<Args>>::call_once::hdbb9ff71143eaad6
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/alloc/src/boxed.rs:1328:9
[INFO] [stdout]   36:     0x563d595c9d6a - <alloc::boxed::Box<F,A> as core::ops::function::FnOnce<Args>>::call_once::h9dbde95cefb8368c
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/alloc/src/boxed.rs:1328:9
[INFO] [stdout]   37:     0x563d595c9d6a - std::sys::unix::thread::Thread::new::thread_start::hc76032c38affd972
[INFO] [stdout]                                at /rustc/25b3db3aa752d9d4633c983c9d4bf5e48f9baff1/library/std/src/sys/unix/thread.rs:71:17
[INFO] [stdout]   38:     0x7f80ab3c1609 - start_thread
[INFO] [stdout]   39:     0x7f80ab193293 - clone
[INFO] [stdout]   40:                0x0 - <unknown>
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] failures:
[INFO] [stdout]     parse_dump_parse_stdlib
[INFO] [stdout] 
[INFO] [stdout] test result: FAILED. 3 passed; 1 failed; 0 ignored; 0 measured; 0 filtered out; finished in 5.54s
[INFO] [stdout] 
[INFO] [stderr] error: test failed, to rerun pass '--test parse'
[INFO] running `Command { std: "docker" "inspect" "98cf90747fe86230a038bf11b04a65b6ddeb1e46d18903cc047757f74e64f09c", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "rm" "-f" "98cf90747fe86230a038bf11b04a65b6ddeb1e46d18903cc047757f74e64f09c", kill_on_drop: false }`
[INFO] [stdout] 98cf90747fe86230a038bf11b04a65b6ddeb1e46d18903cc047757f74e64f09c