additional

config.json

@@ -0,0 +1,3 @@
+{
+  "_name_or_path": "hahunavth/sb-slu-direct-default"
+}

handler.py

@@ -0,0 +1,127 @@
+
+
+import torch
+import speechbrain as sb
+from hyperpyyaml import load_hyperpyyaml
+from speechbrain.utils.distributed import run_on_main
+
+show_results_every = 100  # plots results every N iterations
+run_opts = {
+    "device": "cuda" if torch.cuda.is_available() else "cpu"
+}
+
+class PipelineSLUTask(sb.pretrained.interfaces.Pretrained):
+    HPARAMS_NEEDED = [
+            "slu_enc",
+            "output_emb",
+            "dec",
+            "seq_lin",
+            "env_corrupt",
+            "tokenizer",
+    ]
+    MODULES_NEEDED = [
+            "slu_enc",
+            "output_emb",
+            "dec",
+            "seq_lin",
+            "env_corrupt",
+    ]
+
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        pass
+
+    def encode_file(self, path):
+
+        tokens_bos = torch.tensor([[0]]).to(self.device)
+        tokens = torch.tensor([], dtype=torch.int64).to(self.device)
+
+        waveform = self.load_audio(path)
+        wavs = waveform.unsqueeze(0)
+        wav_lens = torch.tensor([1.0])
+        # Fake a batch:
+        # batch = waveform.unsqueeze(0)
+        rel_length = torch.tensor([1.0])
+        with torch.no_grad():
+            rel_lens = rel_length.to(self.device)
+            # ASR encoder forward pass
+            ASR_encoder_out = self.hparams.asr_model.encode_batch(
+                wavs.detach(), wav_lens
+            )
+
+            # SLU forward pass
+            encoder_out = self.hparams.slu_enc(ASR_encoder_out)
+            e_in = self.hparams.output_emb(tokens_bos)
+            # print(e_in.shape)
+            # print(encoder_out.shape)
+            # print(wav_lens.shape)
+            h, _ = self.hparams.dec(e_in, encoder_out, wav_lens)
+
+            # Output layer for seq2seq log-probabilities
+            logits = self.hparams.seq_lin(h)
+            p_seq = self.hparams.log_softmax(logits)
+
+            # Compute outputs
+            # if (
+            #     stage == sb.Stage.TRAIN
+            #     and self.batch_count % show_results_every != 0
+            # ):
+            #     return p_seq, wav_lens
+            # else:
+            p_tokens, scores = self.hparams.beam_searcher(encoder_out, wav_lens)
+            return p_seq, wav_lens, p_tokens
+
+        # return ASR_encoder_out
+
+    def decode(self, p_seq, wav_lens, predicted_tokens):
+        tokens_eos = torch.tensor([[0]]).to(self.device)
+        tokens_eos_lens = torch.tensor([0]).to(self.device)
+
+        # Decode token terms to words
+        predicted_semantics = [
+            self.hparams.tokenizer.decode_ids(utt_seq).split(" ")
+            for utt_seq in predicted_tokens
+        ]
+        return predicted_semantics
+
+
+from typing import Dict, List, Any
+
+class EndpointHandler():
+    def __init__(self, path=""):
+        hparams_file = f"{path}/better_tokenizer/1986/hyperparams.yaml"
+        overrides = {}
+        with open(hparams_file) as fin:
+            hparams = load_hyperpyyaml(fin, overrides)
+            
+        run_opts = {
+            "device": "cuda" if torch.cuda.is_available() else "cpu"
+        }
+        
+        # We download and pretrain the tokenizer
+        run_on_main(hparams["pretrainer"].collect_files)
+        hparams["pretrainer"].load_collected(device=run_opts["device"])
+        
+        self.pipeline = PipelineSLUTask(
+            modules=hparams['modules'],
+            hparams=hparams,
+            run_opts=run_opts
+        )
+
+    def __call__(self, data: Dict[str, Any]) -> List[Dict[str, Any]]:
+        """
+       data args:
+            inputs (:obj: `str` | `PIL.Image` | `np.array`)
+            kwargs
+      Return:
+            A :obj:`list` | `dict`: will be serialized and returned
+        """
+        # pseudo
+        # self.model(input)
+        data = data.get("inputs", data)
+        print(data)
+        ps, wl, pt = self.pipeline.encode_file(data)
+        print(ps)
+        print(wl)
+        print(pt)
+        return self.pipeline.decode(ps, wl, pt)

hyperparams.yaml

@@ -1,4 +1,4 @@
-# Generated 2023-06-16 from:
+# Generated 2023-06-18 from:
 # /kaggle/working/direct-train.yaml
 # yamllint disable
 # ############################################################################

log.txt

@@ -0,0 +1,869 @@
+2023-06-18 23:24:00,418 - speechbrain.core - INFO - Beginning experiment!
+2023-06-18 23:24:00,419 - speechbrain.core - INFO - Experiment folder: results/better_tokenizer/1986
+2023-06-18 23:24:04,005 - speechbrain.utils.superpowers - DEBUG - absl-py==1.4.0
+accelerate==0.12.0
+access==1.1.9
+affine==2.4.0
+aiobotocore==2.5.0
+aiofiles==22.1.0
+aiohttp @ file:///home/conda/feedstock_root/build_artifacts/aiohttp_1676292661248/work
+aiohttp-cors==0.7.0
+aioitertools==0.11.0
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+aiosignal @ file:///home/conda/feedstock_root/build_artifacts/aiosignal_1667935791922/work
+aiosqlite==0.19.0
+albumentations==1.3.1
+alembic==1.11.1
+altair==5.0.1
+annoy==1.17.2
+ansiwrap==0.8.4
+anyio @ file:///home/conda/feedstock_root/build_artifacts/anyio_1666191106763/work/dist
+apache-beam==2.46.0
+aplus==0.11.0
+appdirs==1.4.4
+argon2-cffi @ file:///home/conda/feedstock_root/build_artifacts/argon2-cffi_1640817743617/work
+argon2-cffi-bindings @ file:///home/conda/feedstock_root/build_artifacts/argon2-cffi-bindings_1666850768662/work
+array-record==0.2.0
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+asttokens @ file:///home/conda/feedstock_root/build_artifacts/asttokens_1670263926556/work
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+atpublic==3.1.2
+attrs @ file:///home/conda/feedstock_root/build_artifacts/attrs_1683424013410/work
+audioread==3.0.0
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+backcall @ file:///home/conda/feedstock_root/build_artifacts/backcall_1592338393461/work
+backoff==2.2.1
+backports.functools-lru-cache @ file:///home/conda/feedstock_root/build_artifacts/backports.functools_lru_cache_1618230623929/work
+bayesian-optimization==1.4.3
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+beatrix-jupyterlab @ file:///home/kbuilder/miniconda3/conda-bld/dlenv-tf-2-12-gpu_1683597552195/work/packages/beatrix_jupyterlab-2023.58.190319.tar.gz#sha256=5d0d9c77a86fcdd097390e863c1c12fc410cc84ab98b6ee16a43b6a84735e57e
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+-e git+https://github.com/SohierDane/BigQuery_Helper@8615a7f6c1663e7f2d48aa2b32c2dbcb600a440f#egg=bq_helper
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+en-core-web-sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.5.0/en_core_web_sm-3.5.0-py3-none-any.whl#sha256=0964370218b7e1672a30ac50d72cdc6b16f7c867496f1d60925691188f4d2510
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+watchfiles==0.19.0
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+wcwidth @ file:///home/conda/feedstock_root/build_artifacts/wcwidth_1673864653149/work
+webcolors==1.13
+webencodings==0.5.1
+websocket-client @ file:///home/conda/feedstock_root/build_artifacts/websocket-client_1675567828044/work
+websockets==11.0.3
+Werkzeug==2.3.6
+wfdb==4.1.1
+whatthepatch==1.0.5
+widgetsnbextension==3.6.4
+witwidget==1.8.1
+woodwork==0.24.0
+Wordbatch==1.4.9
+wordcloud==1.9.2
+wordsegment==1.3.1
+wrapt==1.14.1
+wurlitzer==3.0.3
+xarray==2023.5.0
+xarray-einstats==0.5.1
+xgboost==1.7.5
+xvfbwrapper==0.2.9
+xxhash==3.2.0
+xyzservices==2023.5.0
+y-py==0.5.9
+yapf==0.33.0
+yarl @ file:///home/conda/feedstock_root/build_artifacts/yarl_1682426574163/work
+ydata-profiling==4.1.2
+yellowbrick==1.5
+ypy-websocket==0.8.2
+zict @ file:///home/conda/feedstock_root/build_artifacts/zict_1681770155528/work
+zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1677313463193/work
+zstandard==0.19.0
+
+
+2023-06-18 23:24:04,356 - speechbrain.utils.parameter_transfer - DEBUG - Collecting files (or symlinks) for pretraining in results/better_tokenizer/1986/save/SLURM_tokenizer.
+2023-06-18 23:24:04,356 - speechbrain.pretrained.fetching - INFO - Fetch 58_unigram.model?dl=1: Using existing file/symlink in results/better_tokenizer/1986/save/SLURM_tokenizer/tokenizer.ckpt.
+2023-06-18 23:24:04,358 - speechbrain.utils.parameter_transfer - INFO - Loading pretrained files for: tokenizer
+2023-06-18 23:24:04,366 - speechbrain.utils.checkpoints - INFO - Loading a checkpoint from results/better_tokenizer/1986/save/CKPT+2023-06-16+12-15-08+00
+2023-06-18 23:24:07,162 - speechbrain.core - INFO - Info: ckpt_interval_minutes arg from hparam file is used
+2023-06-18 23:24:07,183 - speechbrain.core - INFO - 9.3M trainable parameters in SLU
+2023-06-18 23:32:35,953 - speechbrain.pretrained.fetching - INFO - Fetch hyperparams.yaml: Delegating to Huggingface hub, source speechbrain/asr-crdnn-rnnlm-librispeech.
+2023-06-18 23:32:35,959 - urllib3.connectionpool - DEBUG - Resetting dropped connection: huggingface.co
+2023-06-18 23:32:36,118 - urllib3.connectionpool - DEBUG - https://huggingface.co:443 "HEAD /speechbrain/asr-crdnn-rnnlm-librispeech/resolve/main/hyperparams.yaml HTTP/1.1" 200 0
+2023-06-18 23:32:36,119 - speechbrain.pretrained.fetching - INFO - Fetch custom.py: Delegating to Huggingface hub, source speechbrain/asr-crdnn-rnnlm-librispeech.
+2023-06-18 23:32:36,199 - urllib3.connectionpool - DEBUG - https://huggingface.co:443 "HEAD /speechbrain/asr-crdnn-rnnlm-librispeech/resolve/main/custom.py HTTP/1.1" 404 0
+2023-06-18 23:32:43,019 - speechbrain.utils.parameter_transfer - DEBUG - Collecting files (or symlinks) for pretraining in pretrained_models/EncoderDecoderASR-4e23c27d817b14bb418343bfc4c8ad5c.
+2023-06-18 23:32:43,020 - speechbrain.pretrained.fetching - INFO - Fetch normalizer.ckpt: Delegating to Huggingface hub, source speechbrain/asr-crdnn-rnnlm-librispeech.
+2023-06-18 23:32:43,092 - urllib3.connectionpool - DEBUG - https://huggingface.co:443 "HEAD /speechbrain/asr-crdnn-rnnlm-librispeech/resolve/main/normalizer.ckpt HTTP/1.1" 302 0
+2023-06-18 23:32:43,093 - speechbrain.pretrained.fetching - INFO - Fetch asr.ckpt: Delegating to Huggingface hub, source speechbrain/asr-crdnn-rnnlm-librispeech.
+2023-06-18 23:32:43,163 - urllib3.connectionpool - DEBUG - https://huggingface.co:443 "HEAD /speechbrain/asr-crdnn-rnnlm-librispeech/resolve/main/asr.ckpt HTTP/1.1" 302 0
+2023-06-18 23:32:43,164 - speechbrain.pretrained.fetching - INFO - Fetch lm.ckpt: Delegating to Huggingface hub, source speechbrain/asr-crdnn-rnnlm-librispeech.
+2023-06-18 23:32:43,236 - urllib3.connectionpool - DEBUG - https://huggingface.co:443 "HEAD /speechbrain/asr-crdnn-rnnlm-librispeech/resolve/main/lm.ckpt HTTP/1.1" 302 0
+2023-06-18 23:32:43,238 - speechbrain.pretrained.fetching - INFO - Fetch tokenizer.ckpt: Delegating to Huggingface hub, source speechbrain/asr-crdnn-rnnlm-librispeech.
+2023-06-18 23:32:43,319 - urllib3.connectionpool - DEBUG - https://huggingface.co:443 "HEAD /speechbrain/asr-crdnn-rnnlm-librispeech/resolve/main/tokenizer.ckpt HTTP/1.1" 302 0
+2023-06-18 23:32:43,321 - speechbrain.utils.parameter_transfer - INFO - Loading pretrained files for: normalizer, asr, lm, tokenizer
+2023-06-18 23:32:47,083 - speechbrain.utils.parameter_transfer - DEBUG - Collecting files (or symlinks) for pretraining in results/better_tokenizer/1986/save/SLURM_tokenizer.
+2023-06-18 23:32:47,083 - speechbrain.pretrained.fetching - INFO - Fetch 58_unigram.model?dl=1: Downloading from normal URL https://www.dropbox.com/s/tmwq12r5vgcsif9/58_unigram.model?dl=1.
+2023-06-18 23:32:48,200 - speechbrain.utils.parameter_transfer - INFO - Loading pretrained files for: tokenizer
+2023-06-18 23:32:48,228 - speechbrain.pretrained.fetching - INFO - Fetch audio-1502897056-headset.flac: Linking to local file in /kaggle/working/slurp/slurp_real/audio-1502897056-headset.flac.

requirements.txt

@@ -0,0 +1,4 @@
+
+speechbrain
+jsonlines
+gdown