Training in progress, step 1

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+jax/jaxlib-0.4.23.dev20240116-cp310-cp310-manylinux2014_x86_64.whl filter=lfs diff=lfs merge=lfs -text
+v8-compile-cache-0/11.3.244.8-node.16/zSoptzScondazSsharezSjupyterzSlabzSstagingzSnode_moduleszSwebpackzSbinzSwebpack.js.BLOB filter=lfs diff=lfs merge=lfs -text

clean-layer.sh

@@ -0,0 +1,24 @@
+#!/bin/bash
+#
+# This scripts should be called at the end of each RUN command
+# in the Dockerfiles.
+#
+# Each RUN command creates a new layer that is stored separately.
+# At the end of each command, we should ensure we clean up downloaded
+# archives and source files used to produce binary to reduce the size
+# of the layer.
+set -e
+set -x
+
+# Delete files that pip caches when installing a package.
+rm -rf /root/.cache/pip/*
+# Delete old downloaded archive files 
+apt-get autoremove -y
+# Delete downloaded archive files
+apt-get clean
+# Ensures the current working directory won't be deleted
+cd /usr/local/src/
+# Delete source files used for building binaries
+rm -rf /usr/local/src/*
+# Delete conda downloaded tarballs
+conda clean -y --tarballs

config.json

@@ -0,0 +1,82 @@
+{
+  "_name_or_path": "facebook/w2v-bert-2.0",
+  "activation_dropout": 0.0,
+  "adapter_act": "relu",
+  "adapter_kernel_size": 3,
+  "adapter_stride": 2,
+  "add_adapter": true,
+  "apply_spec_augment": false,
+  "architectures": [
+    "Wav2Vec2BertForCTC"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "classifier_proj_size": 768,
+  "codevector_dim": 768,
+  "conformer_conv_dropout": 0.1,
+  "contrastive_logits_temperature": 0.1,
+  "conv_depthwise_kernel_size": 31,
+  "ctc_loss_reduction": "mean",
+  "ctc_zero_infinity": true,
+  "diversity_loss_weight": 0.1,
+  "eos_token_id": 2,
+  "feat_proj_dropout": 0.0,
+  "feat_quantizer_dropout": 0.0,
+  "feature_projection_input_dim": 160,
+  "final_dropout": 0.1,
+  "hidden_act": "swish",
+  "hidden_dropout": 0.0,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "layer_norm_eps": 1e-05,
+  "layerdrop": 0.0,
+  "left_max_position_embeddings": 64,
+  "mask_feature_length": 10,
+  "mask_feature_min_masks": 0,
+  "mask_feature_prob": 0.0,
+  "mask_time_length": 10,
+  "mask_time_min_masks": 2,
+  "mask_time_prob": 0.0,
+  "max_source_positions": 5000,
+  "model_type": "wav2vec2-bert",
+  "num_adapter_layers": 1,
+  "num_attention_heads": 16,
+  "num_codevector_groups": 2,
+  "num_codevectors_per_group": 320,
+  "num_hidden_layers": 24,
+  "num_negatives": 100,
+  "output_hidden_size": 1024,
+  "pad_token_id": 41,
+  "position_embeddings_type": "relative_key",
+  "proj_codevector_dim": 768,
+  "right_max_position_embeddings": 8,
+  "rotary_embedding_base": 10000,
+  "tdnn_dilation": [
+    1,
+    2,
+    3,
+    1,
+    1
+  ],
+  "tdnn_dim": [
+    512,
+    512,
+    512,
+    512,
+    1500
+  ],
+  "tdnn_kernel": [
+    5,
+    3,
+    3,
+    1,
+    1
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.39.3",
+  "use_intermediate_ffn_before_adapter": false,
+  "use_weighted_layer_sum": false,
+  "vocab_size": 44,
+  "xvector_output_dim": 512
+}

core-js-banners

@@ -0,0 +1 @@
+["\u001b[96mThank you for using core-js (\u001b[94m https://github.com/zloirock/core-js \u001b[96m) for polyfilling JavaScript standard library!\u001b[0m\n\n\u001b[96mThe project needs your help! Please consider supporting of core-js:\u001b[0m\n\u001b[96m>\u001b[94m https://opencollective.com/core-js \u001b[0m\n\u001b[96m>\u001b[94m https://patreon.com/zloirock \u001b[0m\n\u001b[96m>\u001b[94m https://paypal.me/zloirock \u001b[0m\n\u001b[96m>\u001b[94m bitcoin: bc1qlea7544qtsmj2rayg0lthvza9fau63ux0fstcz \u001b[0m\n\n\u001b[96mAlso, the author of core-js (\u001b[94m https://github.com/zloirock \u001b[96m) is looking for a good job -)\u001b[0m\n","\u001b[96mThank you for using core-js (\u001b[94m https://github.com/zloirock/core-js \u001b[96m) for polyfilling JavaScript standard library!\u001b[0m\n\n\u001b[96mThe project needs your help! Please consider supporting of core-js:\u001b[0m\n\u001b[96m>\u001b[94m https://opencollective.com/core-js \u001b[0m\n\u001b[96m>\u001b[94m https://patreon.com/zloirock \u001b[0m\n\u001b[96m>\u001b[94m bitcoin: bc1qlea7544qtsmj2rayg0lthvza9fau63ux0fstcz \u001b[0m\n\n\u001b[96mAlso, the author of core-js (\u001b[94m https://github.com/zloirock \u001b[96m) is looking for a good job -)\u001b[0m\n"]

jax/jaxlib-0.4.23.dev20240116-cp310-cp310-manylinux2014_x86_64.whl

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+size 130914397

keras_patch.sh

@@ -0,0 +1,41 @@
+#!/bin/bash
+
+# The following "sed" are to patch the current version of tf-df with
+# a fix for keras 3. In essence, replaces the use of package name "tf.keras" with 
+# "tf_keras"
+
+sed -i "/import tensorflow_decision_forests as tfdf/a import tf_keras" /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/__init__.py && \
+sed -i -e "/import tensorflow as tf/a import tf_keras" \
+       -e "/from yggdrasil_decision_forests.utils.distribute.implementations.grpc/a from tensorflow_decision_forests.keras import keras_internal" \
+       -e '/try:/{:a;N;/backend = tf.keras.backend/!ba;d}'\
+       /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/core.py && \
+sed -i -e "s/from typing import Optional, List, Dict, Any, Union, NamedTuple/from typing import Any, Dict, List, NamedTuple, Optional, Union/g" \
+       -e "/import tensorflow as tf/a from tensorflow_decision_forests.keras import keras_internal" \
+       -e "/import tensorflow as tf/a import tf_keras" \
+       -e '/layers = tf.keras.layers/{:a;N;/backend = tf.keras.backend/!ba;d}' \
+       /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/core_inference.py && \
+find /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests -type f -exec sed -i \
+     -e "s/get_data_handler/keras_internal.get_data_handler/g" \
+     -e 's/"models.Functional"/keras_internal.Functional/g' \
+     -e "s/tf.keras.utils.unpack_x_y_sample_weight/keras_internal.unpack_x_y_sample_weight/g" \
+     -e "s/tf.keras.utils.experimental/keras_internal/g" \
+     {} \; && \
+sed -i -e "/import tensorflow as tf/a import tf_keras" \
+       -e "/from tensorflow_decision_forests.keras import core/a from tensorflow_decision_forests.keras import keras_internal" \
+       -e '/layers = tf.keras.layers/{:a;N;/callbacks = tf.keras.callbacks/!ba;d}' \
+       /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/keras_test.py && \
+find /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras -type f -exec sed -i \
+     -e "s/ layers.Input/ tf_keras.layers.Input/g" \
+     -e "s/layers.minimum/tf_keras.layers.minimum/g" \
+     -e "s/layers.Concatenate/tf_keras.layers.Concatenate/g" \
+     -e "s/layers.Dense/tf_keras.layers.Dense/g" \
+     -e "s/layers.experimental.preprocessing./tf_keras.layers./g" \
+     -e "s/layers.DenseFeatures/keras_internal.layers.DenseFeatures/g" \
+     -e "s/models.Model/tf_keras.models.Model/g" {} \; && \
+sed -i "s/ models.load_model/ tf_keras.models.load_model/g" /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/keras_test.py && \
+sed -i "/import tensorflow as tf/a import tf_keras" /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/test_runner.py && \
+sed -i "/import tensorflow as tf/a import tf_keras" /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/wrappers.py && \
+sed -i -e "/import tensorflow as tf/a import tf_keras" \
+       -e "s/optimizer=optimizers.Adam()/optimizer=tf_keras.optimizers.Adam()/g" \
+       /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests/keras/wrappers_pre_generated.py && \
+find /opt/conda/lib/python3.10/site-packages/tensorflow_decision_forests -type f -exec sed -i "s/tf.keras./tf_keras./g" {} \;

model.safetensors

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package_list

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+# This file may be used to create an environment using:
+# $ conda create --name <env> --file <this file>
+# platform: linux-64
+_libgcc_mutex=0.1=conda_forge
+_openmp_mutex=4.5=2_gnu
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preprocessor_config.json

@@ -0,0 +1,10 @@
+{
+  "feature_extractor_type": "SeamlessM4TFeatureExtractor",
+  "feature_size": 80,
+  "num_mel_bins": 80,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "return_attention_mask": true,
+  "sampling_rate": 16000,
+  "stride": 2
+}

runs/Sep06_12-52-37_28ff9dc92ceb/events.out.tfevents.1725628234.28ff9dc92ceb.25.0

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1b0bcddcc74d38a68c476fc6b7c384e1729c87a09eecae9e1b103f00858c31ce
+size 4184

tmp_ncajaqo/_remote_module_non_scriptable.py

@@ -0,0 +1,81 @@
+from typing import *
+
+import torch
+import torch.distributed.rpc as rpc
+from torch import Tensor
+from torch._jit_internal import Future
+from torch.distributed.rpc import RRef
+from typing import Tuple  # pyre-ignore: unused import
+
+
+module_interface_cls = None
+
+
+def forward_async(self, *args, **kwargs):
+    args = (self.module_rref, self.device, self.is_device_map_set, *args)
+    kwargs = {**kwargs}
+    return rpc.rpc_async(
+        self.module_rref.owner(),
+        _remote_forward,
+        args,
+        kwargs,
+    )
+
+
+def forward(self, *args, **kwargs):
+    args = (self.module_rref, self.device, self.is_device_map_set, *args)
+    kwargs = {**kwargs}
+    ret_fut = rpc.rpc_async(
+        self.module_rref.owner(),
+        _remote_forward,
+        args,
+        kwargs,
+    )
+    return ret_fut.wait()
+
+
+_generated_methods = [
+    forward_async,
+    forward,
+]
+
+
+
+
+def _remote_forward(
+    module_rref: RRef[module_interface_cls], device: str, is_device_map_set: bool, *args, **kwargs):
+    module = module_rref.local_value()
+    device = torch.device(device)
+
+    if device.type != "cuda":
+        return module.forward(*args, **kwargs)
+
+    # If the module is on a cuda device,
+    # move any CPU tensor in args or kwargs to the same cuda device.
+    # Since torch script does not support generator expression,
+    # have to use concatenation instead of
+    # ``tuple(i.to(device) if isinstance(i, Tensor) else i for i in *args)``.
+    args = (*args,)
+    out_args: Tuple[()] = ()
+    for arg in args:
+        arg = (arg.to(device),) if isinstance(arg, Tensor) else (arg,)
+        out_args = out_args + arg
+
+    kwargs = {**kwargs}
+    for k, v in kwargs.items():
+        if isinstance(v, Tensor):
+            kwargs[k] = kwargs[k].to(device)
+
+    if is_device_map_set:
+        return module.forward(*out_args, **kwargs)
+
+    # If the device map is empty, then only CPU tensors are allowed to send over wire,
+    # so have to move any GPU tensor to CPU in the output.
+    # Since torch script does not support generator expression,
+    # have to use concatenation instead of
+    # ``tuple(i.cpu() if isinstance(i, Tensor) else i for i in module.forward(*out_args, **kwargs))``.
+    ret: Tuple[()] = ()
+    for i in module.forward(*out_args, **kwargs):
+        i = (i.cpu(),) if isinstance(i, Tensor) else (i,)
+        ret = ret + i
+    return ret

tmp_v_7l1kw.json

@@ -0,0 +1,12 @@
+{
+  "shell_port": 33201,
+  "iopub_port": 43183,
+  "stdin_port": 52051,
+  "control_port": 40843,
+  "hb_port": 54269,
+  "ip": "127.0.0.1",
+  "key": "6620e19b-5fdfd5174441d18476e7b0e7",
+  "transport": "tcp",
+  "signature_scheme": "hmac-sha256",
+  "kernel_name": "python3"
+}

training_args.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:306b30570f912eecde8991d8d3337d7e0e054002ec7bcdf9df74086c94fc68ef
+size 4856

v8-compile-cache-0/11.3.244.8-node.16/zSoptzScondazSsharezSjupyterzSlabzSstagingzSnode_moduleszSwebpackzSbinzSwebpack.js.BLOB

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0e1d585bb02b985ec668a78261aed811e24963f00ac15bf945a945de1f32f956
+size 4604272

yarn--1704964927164-0.1782869183766309/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704964927165-0.35993847591915795/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704964927165-0.35993847591915795/yarn

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "/opt/conda/share/jupyter/lab/staging/yarn.js" "$@"

yarn--1704964928127-0.35887085411210307/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704964928127-0.35887085411210307/yarn

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "/opt/conda/share/jupyter/lab/staging/yarn.js" "$@"

yarn--1704964933548-0.9586437363349738/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704964933548-0.9586437363349738/yarn

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "/opt/conda/share/jupyter/lab/staging/yarn.js" "$@"

yarn--1704965062369-0.2181574829625219/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704965062369-0.2181574829625219/yarn

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "/opt/conda/share/jupyter/lab/staging/yarn.js" "$@"

yarn--1704965063359-0.7469983285256505/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704965063359-0.7469983285256505/yarn

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "/opt/conda/share/jupyter/lab/staging/yarn.js" "$@"

yarn--1704965068891-0.46018400452963615/node

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "$@"

yarn--1704965068891-0.46018400452963615/yarn

@@ -0,0 +1,3 @@
+#!/bin/sh
+
+exec "/opt/conda/bin/node" "/opt/conda/share/jupyter/lab/staging/yarn.js" "$@"