[INFO] fetching crate embedding 0.1.5...
[INFO] fixing embedding-0.1.5 against try#622891a4e29178280638a6b63a8908bde2c0c854+cargoflags=-Zfix-edition=start=2015 for pr-157817-2
[INFO] extracting crate embedding 0.1.5 into /workspace/builds/worker-7-tc1/source
[INFO] started tweaking crates.io crate embedding 0.1.5
[INFO] removed 0 missing examples
[INFO] removed 0 missing tests
[INFO] finished tweaking crates.io crate embedding 0.1.5
[INFO] tweaked toml for crates.io crate embedding 0.1.5 written to /workspace/builds/worker-7-tc1/source/Cargo.toml
[INFO] validating manifest of crates.io crate embedding 0.1.5 on toolchain 622891a4e29178280638a6b63a8908bde2c0c854
[INFO] running `Command { std: CARGO_HOME="/workspace/cargo-home" RUSTUP_HOME="/workspace/rustup-home" "/workspace/cargo-home/bin/cargo" "+622891a4e29178280638a6b63a8908bde2c0c854" "metadata" "--manifest-path" "Cargo.toml" "--no-deps", kill_on_drop: false }`
[INFO] crate crates.io crate embedding 0.1.5 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" "+622891a4e29178280638a6b63a8908bde2c0c854" "fetch" "--manifest-path" "Cargo.toml", kill_on_drop: false }`
[INFO] [stderr]     Blocking waiting for file lock on package cache
[INFO] [stderr]     Updating crates.io index
[INFO] [stderr]  Downloading crates ...
[INFO] [stderr]   Downloaded ndarray-rand v0.15.0
[INFO] running `Command { std: "docker" "create" "-v" "/var/lib/crater-agent-workspace/builds/worker-7-tc1/source:/opt/rustwide/workdir:rw,Z" "-v" "/var/lib/crater-agent-workspace/builds/worker-7-tc1/target:/opt/rustwide/target:rw,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" "-m" "1610612736" "--network" "none" "ghcr.io/rust-lang/crates-build-env/linux@sha256:3a6becf2bc8dde7f3fa57ede90e4f284e72d296796fc446bbb1e2c7cc0530151" "sleep" "infinity", kill_on_drop: false }`
[INFO] [stdout] baca6622b6e77b863311259fe0fdee30e89c8a8acede5b351aca0b71fea443d2
[INFO] running `Command { std: "docker" "start" "baca6622b6e77b863311259fe0fdee30e89c8a8acede5b351aca0b71fea443d2", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "exec" "-e" "SOURCE_DIR=/opt/rustwide/workdir" "-e" "CARGO_HOME=/opt/rustwide/cargo-home" "-e" "RUSTUP_HOME=/opt/rustwide/rustup-home" "-e" "CARGO_TARGET_DIR=/opt/rustwide/target" "-w" "/opt/rustwide/workdir" "--user" "0:0" "baca6622b6e77b863311259fe0fdee30e89c8a8acede5b351aca0b71fea443d2" "/opt/rustwide/cargo-home/bin/cargo" "+622891a4e29178280638a6b63a8908bde2c0c854" "metadata" "--no-deps" "--format-version=1", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "inspect" "baca6622b6e77b863311259fe0fdee30e89c8a8acede5b351aca0b71fea443d2", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "exec" "-e" "SOURCE_DIR=/opt/rustwide/workdir" "-e" "CARGO_HOME=/opt/rustwide/cargo-home" "-e" "RUSTUP_HOME=/opt/rustwide/rustup-home" "-e" "CARGO_TARGET_DIR=/opt/rustwide/target" "-e" "CARGO_INCREMENTAL=0" "-e" "RUST_BACKTRACE=full" "-e" "RUSTFLAGS=" "-e" "RUSTDOCFLAGS=" "-w" "/opt/rustwide/workdir" "--user" "0:0" "baca6622b6e77b863311259fe0fdee30e89c8a8acede5b351aca0b71fea443d2" "/opt/rustwide/cargo-home/bin/cargo" "+622891a4e29178280638a6b63a8908bde2c0c854" "fix" "--allow-no-vcs" "--allow-dirty" "--frozen" "--all" "--all-targets" "--message-format=json" "-Zfix-edition=start=2015", kill_on_drop: false }`
[INFO] [stderr]    Compiling either v1.16.0
[INFO] [stderr]    Compiling matrixmultiply v0.3.10
[INFO] [stderr]    Compiling regex-syntax v0.8.11
[INFO] [stderr]    Compiling zerocopy-derive v0.8.52
[INFO] [stderr]    Compiling rustix v1.1.4
[INFO] [stderr]     Checking rawpointer v0.2.1
[INFO] [stderr]    Compiling petgraph v0.7.1
[INFO] [stderr]     Checking num-complex v0.4.6
[INFO] [stderr]     Checking num-integer v0.1.46
[INFO] [stderr]    Compiling log v0.4.32
[INFO] [stderr]    Compiling clap_derive v4.6.1
[INFO] [stderr]     Checking tracing-subscriber v0.3.23
[INFO] [stderr]     Checking regex-automata v0.4.14
[INFO] [stderr]     Checking bincode v1.3.3
[INFO] [stderr]     Checking memmap2 v0.9.10
[INFO] [stderr]     Checking plotters v0.3.7
[INFO] [stderr]     Checking tinytemplate v1.2.1
[INFO] [stderr]    Compiling itertools v0.14.0
[INFO] [stderr]     Checking ndarray v0.16.1
[INFO] [stderr]     Checking ndarray v0.15.6
[INFO] [stderr]     Checking clap v4.6.1
[INFO] [stderr]     Checking zerocopy v0.8.52
[INFO] [stderr]    Compiling tempfile v3.27.0
[INFO] [stderr]     Checking regex v1.12.4
[INFO] [stderr]    Compiling prost-derive v0.13.5
[INFO] [stderr]    Compiling prost v0.13.5
[INFO] [stderr]    Compiling prost-types v0.13.5
[INFO] [stderr]    Compiling prost-build v0.13.5
[INFO] [stderr]    Compiling embedding v0.1.5 (/opt/rustwide/workdir)
[INFO] [stderr]     Checking ppv-lite86 v0.2.21
[INFO] [stderr]     Checking half v2.7.1
[INFO] [stderr]     Checking ciborium-ll v0.2.2
[INFO] [stderr]     Checking rand_chacha v0.3.1
[INFO] [stderr]     Checking rand_chacha v0.9.0
[INFO] [stderr]     Checking ciborium v0.2.2
[INFO] [stderr]     Checking rand v0.8.6
[INFO] [stderr]     Checking proptest v1.11.0
[INFO] [stderr]     Checking criterion v0.5.1
[INFO] [stderr]     Checking rand_distr v0.4.3
[INFO] [stderr]     Checking ndarray-rand v0.15.0
[INFO] [stdout] warning: unused import: `crate::mmap`
[INFO] [stdout]  --> src/model.rs:7:5
[INFO] [stdout]   |
[INFO] [stdout] 7 | use crate::mmap;
[INFO] [stdout]   |     ^^^^^^^^^^^
[INFO] [stdout]   |
[INFO] [stdout]   = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `ndarray::Array`
[INFO] [stdout]  --> src/training.rs:1:5
[INFO] [stdout]   |
[INFO] [stdout] 1 | use ndarray::Array;
[INFO] [stdout]   |     ^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `index_start`
[INFO] [stdout]    --> src/mmap.rs:170:9
[INFO] [stdout]     |
[INFO] [stdout] 170 |     let index_start = file.metadata().map_err(|e| e.to_string())?.len() as usize;
[INFO] [stdout]     |         ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_index_start`
[INFO] [stdout]     |
[INFO] [stdout]     = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `data_start`
[INFO] [stdout]    --> src/mmap.rs:186:9
[INFO] [stdout]     |
[INFO] [stdout] 186 |     let data_start = file.metadata().map_err(|e| e.to_string())?.len() as usize;
[INFO] [stdout]     |         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_data_start`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: methods `accumulate_gradient`, `apply_merged_gradients`, and `l2_grad` are never used
[INFO] [stdout]    --> src/training.rs:269:8
[INFO] [stdout]     |
[INFO] [stdout]  12 | impl EmbeddingModel {
[INFO] [stdout]     | ------------------- methods in this implementation
[INFO] [stdout] ...
[INFO] [stdout] 269 |     fn accumulate_gradient(&self, accum: &mut HashMap<usize, Vec<f32>>, word_id: usize, grad: f32, dim_idx: usize) {
[INFO] [stdout]     |        ^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 284 |     fn apply_merged_gradients(&mut self, merged: &HashMap<usize, Vec<f32>>, count: usize) {
[INFO] [stdout]     |        ^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 518 |     fn l2_grad(&self, grad: f32, learning_rate: f32, weight: f32) -> f32 {
[INFO] [stdout]     |        ^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: `#[warn(dead_code)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing field `word_freq` in initializer of `embedding::TrainingData`
[INFO] [stdout]   --> benches/embedding_bench.rs:13:25
[INFO] [stdout]    |
[INFO] [stdout] 13 |     let training_data = TrainingData {
[INFO] [stdout]    |                         ^^^^^^^^^^^^ missing `word_freq`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing fields `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields in initializer of `embedding::TrainingConfig`
[INFO] [stdout]   --> benches/embedding_bench.rs:19:18
[INFO] [stdout]    |
[INFO] [stdout] 19 |     let config = TrainingConfig {
[INFO] [stdout]    |                  ^^^^^^^^^^^^^^ missing `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing field `word_freq` in initializer of `embedding::TrainingData`
[INFO] [stdout]   --> benches/embedding_bench.rs:52:25
[INFO] [stdout]    |
[INFO] [stdout] 52 |     let training_data = TrainingData {
[INFO] [stdout]    |                         ^^^^^^^^^^^^ missing `word_freq`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing fields `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields in initializer of `embedding::TrainingConfig`
[INFO] [stdout]   --> benches/embedding_bench.rs:58:18
[INFO] [stdout]    |
[INFO] [stdout] 58 |     let config = TrainingConfig {
[INFO] [stdout]    |                  ^^^^^^^^^^^^^^ missing `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing field `word_freq` in initializer of `embedding::TrainingData`
[INFO] [stdout]   --> benches/embedding_bench.rs:91:25
[INFO] [stdout]    |
[INFO] [stdout] 91 |     let training_data = TrainingData {
[INFO] [stdout]    |                         ^^^^^^^^^^^^ missing `word_freq`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing fields `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields in initializer of `embedding::TrainingConfig`
[INFO] [stdout]   --> benches/embedding_bench.rs:97:18
[INFO] [stdout]    |
[INFO] [stdout] 97 |     let config = TrainingConfig {
[INFO] [stdout]    |                  ^^^^^^^^^^^^^^ missing `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing field `word_freq` in initializer of `embedding::TrainingData`
[INFO] [stdout]    --> benches/embedding_bench.rs:131:25
[INFO] [stdout]     |
[INFO] [stdout] 131 |     let training_data = TrainingData {
[INFO] [stdout]     |                         ^^^^^^^^^^^^ missing `word_freq`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing fields `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields in initializer of `embedding::TrainingConfig`
[INFO] [stdout]    --> benches/embedding_bench.rs:137:18
[INFO] [stdout]     |
[INFO] [stdout] 137 |     let config = TrainingConfig {
[INFO] [stdout]     |                  ^^^^^^^^^^^^^^ missing `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing field `word_freq` in initializer of `embedding::TrainingData`
[INFO] [stdout]    --> benches/embedding_bench.rs:186:25
[INFO] [stdout]     |
[INFO] [stdout] 186 |     let training_data = TrainingData {
[INFO] [stdout]     |                         ^^^^^^^^^^^^ missing `word_freq`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing fields `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields in initializer of `embedding::TrainingConfig`
[INFO] [stdout]    --> benches/embedding_bench.rs:192:18
[INFO] [stdout]     |
[INFO] [stdout] 192 |     let config = TrainingConfig {
[INFO] [stdout]     |                  ^^^^^^^^^^^^^^ missing `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing field `word_freq` in initializer of `embedding::TrainingData`
[INFO] [stdout]    --> benches/embedding_bench.rs:226:25
[INFO] [stdout]     |
[INFO] [stdout] 226 |     let training_data = TrainingData {
[INFO] [stdout]     |                         ^^^^^^^^^^^^ missing `word_freq`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing fields `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields in initializer of `embedding::TrainingConfig`
[INFO] [stdout]    --> benches/embedding_bench.rs:232:18
[INFO] [stdout]     |
[INFO] [stdout] 232 |     let config = TrainingConfig {
[INFO] [stdout]     |                  ^^^^^^^^^^^^^^ missing `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing field `word_freq` in initializer of `embedding::TrainingData`
[INFO] [stdout]    --> benches/embedding_bench.rs:266:25
[INFO] [stdout]     |
[INFO] [stdout] 266 |     let training_data = TrainingData {
[INFO] [stdout]     |                         ^^^^^^^^^^^^ missing `word_freq`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing fields `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields in initializer of `embedding::TrainingConfig`
[INFO] [stdout]    --> benches/embedding_bench.rs:272:18
[INFO] [stdout]     |
[INFO] [stdout] 272 |     let config = TrainingConfig {
[INFO] [stdout]     |                  ^^^^^^^^^^^^^^ missing `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing field `word_freq` in initializer of `embedding::TrainingData`
[INFO] [stdout]    --> benches/embedding_bench.rs:309:25
[INFO] [stdout]     |
[INFO] [stdout] 309 |     let training_data = TrainingData {
[INFO] [stdout]     |                         ^^^^^^^^^^^^ missing `word_freq`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] error[E0063]: missing fields `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields in initializer of `embedding::TrainingConfig`
[INFO] [stdout]    --> benches/embedding_bench.rs:315:18
[INFO] [stdout]     |
[INFO] [stdout] 315 |     let config = TrainingConfig {
[INFO] [stdout]     |                  ^^^^^^^^^^^^^^ missing `checkpoint_interval`, `checkpoint_path`, `subsample_threshold` and 3 other fields
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] For more information about this error, try `rustc --explain E0063`.
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `crate::mmap`
[INFO] [stdout]  --> src/model.rs:7:5
[INFO] [stdout]   |
[INFO] [stdout] 7 | use crate::mmap;
[INFO] [stdout]   |     ^^^^^^^^^^^
[INFO] [stdout]   |
[INFO] [stdout]   = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `ndarray::Array`
[INFO] [stdout]  --> src/training.rs:1:5
[INFO] [stdout]   |
[INFO] [stdout] 1 | use ndarray::Array;
[INFO] [stdout]   |     ^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stderr] error: could not compile `embedding` (bench "embedding_bench") due to 16 previous errors
[INFO] [stderr] warning: build failed, waiting for other jobs to finish...
[INFO] [stdout] warning: unused variable: `index_start`
[INFO] [stdout]    --> src/mmap.rs:170:9
[INFO] [stdout]     |
[INFO] [stdout] 170 |     let index_start = file.metadata().map_err(|e| e.to_string())?.len() as usize;
[INFO] [stdout]     |         ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_index_start`
[INFO] [stdout]     |
[INFO] [stdout]     = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `data_start`
[INFO] [stdout]    --> src/mmap.rs:186:9
[INFO] [stdout]     |
[INFO] [stdout] 186 |     let data_start = file.metadata().map_err(|e| e.to_string())?.len() as usize;
[INFO] [stdout]     |         ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_data_start`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: methods `accumulate_gradient`, `apply_merged_gradients`, and `l2_grad` are never used
[INFO] [stdout]    --> src/training.rs:269:8
[INFO] [stdout]     |
[INFO] [stdout]  12 | impl EmbeddingModel {
[INFO] [stdout]     | ------------------- methods in this implementation
[INFO] [stdout] ...
[INFO] [stdout] 269 |     fn accumulate_gradient(&self, accum: &mut HashMap<usize, Vec<f32>>, word_id: usize, grad: f32, dim_idx: usize) {
[INFO] [stdout]     |        ^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 284 |     fn apply_merged_gradients(&mut self, merged: &HashMap<usize, Vec<f32>>, count: usize) {
[INFO] [stdout]     |        ^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] ...
[INFO] [stdout] 518 |     fn l2_grad(&self, grad: f32, learning_rate: f32, weight: f32) -> f32 {
[INFO] [stdout]     |        ^^^^^^^
[INFO] [stdout]     |
[INFO] [stdout]     = note: `#[warn(dead_code)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] running `Command { std: "docker" "inspect" "baca6622b6e77b863311259fe0fdee30e89c8a8acede5b351aca0b71fea443d2", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "rm" "-f" "baca6622b6e77b863311259fe0fdee30e89c8a8acede5b351aca0b71fea443d2", kill_on_drop: false }`
[INFO] [stdout] baca6622b6e77b863311259fe0fdee30e89c8a8acede5b351aca0b71fea443d2
