Tapas tf (#13393)

* TF Tapas first commit * updated docs * updated logger message * updated pytorch weight conversion script to support scalar array * added use_cache to tapas model config to work properly with tf input_processing * 1. rm embeddings_sum 2. added # Copied 3. + TFTapasMLMHead 4. and lot other small fixes * updated docs * + test for tapas * updated testing_utils to check is_tensorflow_probability_available * converted model logits post processing using numpy to work with both PT and TF models * + TFAutoModelForTableQuestionAnswering * added TF support * added test for TFAutoModelForTableQuestionAnswering * added test for TFAutoModelForTableQuestionAnswering pipeline * updated auto model docs * fixed typo in import * added tensorflow_probability to run tests * updated MLM head * updated tapas.rst with TF model docs * fixed optimizer import in docs * updated convert to np data from pt model is not `transformers.tokenization_utils_base.BatchEncoding` after pipeline upgrade * updated pipeline: 1. with torch.no_gard removed, pipeline forward handles 2. token_type_ids converted to numpy * updated docs. * removed `use_cache` from config * removed floats_tensor * updated code comment * updated Copyright Year and logits_aggregation Optional * updated docs and comments * updated docstring * fixed model weight loading * make fixup * fix indentation * added tf slow pipeline test * pip upgrade * upgrade python to 3.7 * removed from_pt from tests * revert commit f18cfa9
huggingface · Nov 30, 2021 · c468a87 · c468a87
1 parent 6fc38ad
commit c468a87
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diff --git a/.circleci/config.yml b/.circleci/config.yml
@@ -65,7 +65,7 @@ jobs:
     run_tests_torch_and_tf:
         working_directory: ~/transformers
         docker:
-            - image: circleci/python:3.6
+            - image: circleci/python:3.7
         environment:
             OMP_NUM_THREADS: 1
             RUN_PT_TF_CROSS_TESTS: yes
@@ -82,6 +82,7 @@ jobs:
             - run: pip install --upgrade pip
             - run: pip install .[sklearn,tf-cpu,torch,testing,sentencepiece,torch-speech,vision]
             - run: pip install torch-scatter -f https://pytorch-geometric.com/whl/torch-1.10.0+cpu.html
+            - run: pip install tensorflow_probability
             - save_cache:
                 key: v0.4-{{ checksum "setup.py" }}
                 paths:
@@ -118,6 +119,7 @@ jobs:
             - run: pip install --upgrade pip
             - run: pip install .[sklearn,tf-cpu,torch,testing,sentencepiece,torch-speech,vision]
             - run: pip install torch-scatter -f https://pytorch-geometric.com/whl/torch-1.10.0+cpu.html
+            - run: pip install tensorflow_probability
             - save_cache:
                 key: v0.4-{{ checksum "setup.py" }}
                 paths:
@@ -278,6 +280,7 @@ jobs:
                       - v0.4-{{ checksum "setup.py" }}
             - run: pip install --upgrade pip
             - run: pip install .[sklearn,tf-cpu,testing,sentencepiece,tf-speech,vision]
+            - run: pip install tensorflow_probability
             - save_cache:
                   key: v0.4-tf-{{ checksum "setup.py" }}
                   paths:
@@ -311,6 +314,7 @@ jobs:
                       - v0.4-{{ checksum "setup.py" }}
             - run: pip install --upgrade pip
             - run: pip install .[sklearn,tf-cpu,testing,sentencepiece,tf-speech,vision]
+            - run: pip install tensorflow_probability
             - save_cache:
                   key: v0.4-tf-{{ checksum "setup.py" }}
                   paths:
@@ -468,6 +472,7 @@ jobs:
                       - v0.4-{{ checksum "setup.py" }}
             - run: pip install --upgrade pip
             - run: pip install .[sklearn,tf-cpu,testing,sentencepiece]
+            - run: pip install tensorflow_probability
             - save_cache:
                   key: v0.4-tf-{{ checksum "setup.py" }}
                   paths:
@@ -502,6 +507,7 @@ jobs:
                       - v0.4-{{ checksum "setup.py" }}
             - run: pip install --upgrade pip
             - run: pip install .[sklearn,tf-cpu,testing,sentencepiece]
+            - run: pip install tensorflow_probability
             - save_cache:
                   key: v0.4-tf-{{ checksum "setup.py" }}
                   paths:

diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -499,7 +499,7 @@ Flax), PyTorch, and/or TensorFlow.
 +-----------------------------+----------------+----------------+-----------------+--------------------+--------------+
 |             T5              |       ✅       |       ✅       |       ✅        |         ✅         |      ✅      |
 +-----------------------------+----------------+----------------+-----------------+--------------------+--------------+
-|            TAPAS            |       ✅       |       ❌       |       ✅        |         ❌         |      ❌      |
+|            TAPAS            |       ✅       |       ❌       |       ✅        |         ✅         |      ❌      |
 +-----------------------------+----------------+----------------+-----------------+--------------------+--------------+
 |       Transformer-XL        |       ✅       |       ❌       |       ✅        |         ✅         |      ❌      |
 +-----------------------------+----------------+----------------+-----------------+--------------------+--------------+

diff --git a/docs/source/model_doc/auto.rst b/docs/source/model_doc/auto.rst
@@ -265,6 +265,13 @@ TFAutoModelForMultipleChoice
     :members:
 
 
+TFAutoModelForTableQuestionAnswering
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+.. autoclass:: transformers.TFAutoModelForTableQuestionAnswering
+    :members:
+
+
 TFAutoModelForTokenClassification
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 

diff --git a/docs/source/model_doc/tapas.rst b/docs/source/model_doc/tapas.rst
diff --git a/src/transformers/__init__.py b/src/transformers/__init__.py
@@ -1446,6 +1446,7 @@
             "TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING",
             "TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING",
             "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING",
+            "TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING",
             "TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING",
             "TF_MODEL_MAPPING",
             "TF_MODEL_WITH_LM_HEAD_MAPPING",
@@ -1458,6 +1459,7 @@
             "TFAutoModelForQuestionAnswering",
             "TFAutoModelForSeq2SeqLM",
             "TFAutoModelForSequenceClassification",
+            "TFAutoModelForTableQuestionAnswering",
             "TFAutoModelForTokenClassification",
             "TFAutoModelWithLMHead",
         ]
@@ -1767,6 +1769,16 @@
             "TFT5PreTrainedModel",
         ]
     )
+    _import_structure["models.tapas"].extend(
+        [
+            "TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST",
+            "TFTapasForMaskedLM",
+            "TFTapasForQuestionAnswering",
+            "TFTapasForSequenceClassification",
+            "TFTapasModel",
+            "TFTapasPreTrainedModel",
+        ]
+    )
     _import_structure["models.transfo_xl"].extend(
         [
             "TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST",
@@ -3225,6 +3237,7 @@
             TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
             TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
             TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
+            TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING,
             TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
             TF_MODEL_MAPPING,
             TF_MODEL_WITH_LM_HEAD_MAPPING,
@@ -3237,6 +3250,7 @@
             TFAutoModelForQuestionAnswering,
             TFAutoModelForSeq2SeqLM,
             TFAutoModelForSequenceClassification,
+            TFAutoModelForTableQuestionAnswering,
             TFAutoModelForTokenClassification,
             TFAutoModelWithLMHead,
         )
@@ -3483,6 +3497,14 @@
             TFT5Model,
             TFT5PreTrainedModel,
         )
+        from .models.tapas import (
+            TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
+            TFTapasForMaskedLM,
+            TFTapasForQuestionAnswering,
+            TFTapasForSequenceClassification,
+            TFTapasModel,
+            TFTapasPreTrainedModel,
+        )
         from .models.transfo_xl import (
             TF_TRANSFO_XL_PRETRAINED_MODEL_ARCHIVE_LIST,
             TFAdaptiveEmbedding,

diff --git a/src/transformers/file_utils.py b/src/transformers/file_utils.py
@@ -213,6 +213,14 @@
     _soundfile_available = False
 
 
+_tensorflow_probability_available = importlib.util.find_spec("tensorflow_probability") is not None
+try:
+    _tensorflow_probability_version = importlib_metadata.version("tensorflow_probability")
+    logger.debug(f"Successfully imported tensorflow-probability version {_tensorflow_probability_version}")
+except importlib_metadata.PackageNotFoundError:
+    _tensorflow_probability_available = False
+
+
 _timm_available = importlib.util.find_spec("timm") is not None
 try:
     _timm_version = importlib_metadata.version("timm")
@@ -444,6 +452,10 @@ def is_pytorch_quantization_available():
     return _pytorch_quantization_available
 
 
+def is_tensorflow_probability_available():
+    return _tensorflow_probability_available
+
+
 def is_pandas_available():
     return importlib.util.find_spec("pandas") is not None
 
@@ -629,6 +641,12 @@ def wrapper(*args, **kwargs):
 `pip install pytorch-quantization --extra-index-url https://pypi.ngc.nvidia.com`
 """
 
+# docstyle-ignore
+TENSORFLOW_PROBABILITY_IMPORT_ERROR = """
+{0} requires the tensorflow_probability library but it was not found in your environment. You can install it with pip as
+explained here: https://github.com/tensorflow/probability.
+"""
+
 
 # docstyle-ignore
 PANDAS_IMPORT_ERROR = """
@@ -684,6 +702,7 @@ def wrapper(*args, **kwargs):
         ("sentencepiece", (is_sentencepiece_available, SENTENCEPIECE_IMPORT_ERROR)),
         ("sklearn", (is_sklearn_available, SKLEARN_IMPORT_ERROR)),
         ("speech", (is_speech_available, SPEECH_IMPORT_ERROR)),
+        ("tensorflow_probability", (is_tensorflow_probability_available, TENSORFLOW_PROBABILITY_IMPORT_ERROR)),
         ("tf", (is_tf_available, TENSORFLOW_IMPORT_ERROR)),
         ("timm", (is_timm_available, TIMM_IMPORT_ERROR)),
         ("tokenizers", (is_tokenizers_available, TOKENIZERS_IMPORT_ERROR)),

diff --git a/src/transformers/modeling_tf_pytorch_utils.py b/src/transformers/modeling_tf_pytorch_utils.py
@@ -399,7 +399,9 @@ def load_tf2_weights_in_pytorch_model(pt_model, tf_weights, allow_missing_keys=F
             raise e
 
         # logger.warning(f"Initialize PyTorch weight {pt_weight_name}")
-
+        # Make sure we have a proper numpy array
+        if numpy.isscalar(array):
+            array = numpy.array(array)
         new_pt_params_dict[pt_weight_name] = torch.from_numpy(array)
         loaded_pt_weights_data_ptr[pt_weight.data_ptr()] = torch.from_numpy(array)
         all_tf_weights.discard(pt_weight_name)

diff --git a/src/transformers/models/auto/__init__.py b/src/transformers/models/auto/__init__.py
@@ -83,6 +83,7 @@
         "TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING",
         "TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING",
         "TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING",
+        "TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING",
         "TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING",
         "TF_MODEL_MAPPING",
         "TF_MODEL_WITH_LM_HEAD_MAPPING",
@@ -95,6 +96,7 @@
         "TFAutoModelForQuestionAnswering",
         "TFAutoModelForSeq2SeqLM",
         "TFAutoModelForSequenceClassification",
+        "TFAutoModelForTableQuestionAnswering",
         "TFAutoModelForTokenClassification",
         "TFAutoModelWithLMHead",
     ]
@@ -189,6 +191,7 @@
             TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
             TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
             TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
+            TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING,
             TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
             TF_MODEL_MAPPING,
             TF_MODEL_WITH_LM_HEAD_MAPPING,
@@ -201,6 +204,7 @@
             TFAutoModelForQuestionAnswering,
             TFAutoModelForSeq2SeqLM,
             TFAutoModelForSequenceClassification,
+            TFAutoModelForTableQuestionAnswering,
             TFAutoModelForTokenClassification,
             TFAutoModelWithLMHead,
         )

diff --git a/src/transformers/models/auto/modeling_tf_auto.py b/src/transformers/models/auto/modeling_tf_auto.py
@@ -59,6 +59,7 @@
         ("funnel", ("TFFunnelModel", "TFFunnelBaseModel")),
         ("dpr", "TFDPRQuestionEncoder"),
         ("mpnet", "TFMPNetModel"),
+        ("tapas", "TFTapasModel"),
         ("mbart", "TFMBartModel"),
         ("marian", "TFMarianModel"),
         ("pegasus", "TFPegasusModel"),
@@ -92,6 +93,7 @@
         ("xlm", "TFXLMWithLMHeadModel"),
         ("ctrl", "TFCTRLLMHeadModel"),
         ("electra", "TFElectraForPreTraining"),
+        ("tapas", "TFTapasForMaskedLM"),
         ("funnel", "TFFunnelForPreTraining"),
         ("mpnet", "TFMPNetForMaskedLM"),
     ]
@@ -124,6 +126,7 @@
         ("xlm", "TFXLMWithLMHeadModel"),
         ("ctrl", "TFCTRLLMHeadModel"),
         ("electra", "TFElectraForMaskedLM"),
+        ("tapas", "TFTapasForMaskedLM"),
         ("funnel", "TFFunnelForMaskedLM"),
         ("mpnet", "TFMPNetForMaskedLM"),
     ]
@@ -172,6 +175,7 @@
         ("flaubert", "TFFlaubertWithLMHeadModel"),
         ("xlm", "TFXLMWithLMHeadModel"),
         ("electra", "TFElectraForMaskedLM"),
+        ("tapas", "TFTapasForMaskedLM"),
         ("funnel", "TFFunnelForMaskedLM"),
         ("mpnet", "TFMPNetForMaskedLM"),
     ]
@@ -215,6 +219,7 @@
         ("flaubert", "TFFlaubertForSequenceClassification"),
         ("xlm", "TFXLMForSequenceClassification"),
         ("electra", "TFElectraForSequenceClassification"),
+        ("tapas", "TFTapasForSequenceClassification"),
         ("funnel", "TFFunnelForSequenceClassification"),
         ("gpt2", "TFGPT2ForSequenceClassification"),
         ("mpnet", "TFMPNetForSequenceClassification"),
@@ -249,6 +254,14 @@
     ]
 )
 
+TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING_NAMES = OrderedDict(
+    [
+        # Model for Table Question Answering mapping
+        ("tapas", "TFTapasForQuestionAnswering"),
+    ]
+)
+
+
 TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES = OrderedDict(
     [
         # Model for Token Classification mapping
@@ -323,6 +336,9 @@
 TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING = _LazyAutoMapping(
     CONFIG_MAPPING_NAMES, TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING_NAMES
 )
+TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING = _LazyAutoMapping(
+    CONFIG_MAPPING_NAMES, TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING_NAMES
+)
 TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING = _LazyAutoMapping(
     CONFIG_MAPPING_NAMES, TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING_NAMES
 )
@@ -402,6 +418,17 @@ class TFAutoModelForQuestionAnswering(_BaseAutoModelClass):
 TFAutoModelForQuestionAnswering = auto_class_update(TFAutoModelForQuestionAnswering, head_doc="question answering")
 
 
+class TFAutoModelForTableQuestionAnswering(_BaseAutoModelClass):
+    _model_mapping = TF_MODEL_FOR_TABLE_QUESTION_ANSWERING_MAPPING
+
+
+TFAutoModelForTableQuestionAnswering = auto_class_update(
+    TFAutoModelForTableQuestionAnswering,
+    head_doc="table question answering",
+    checkpoint_for_example="google/tapas-base-finetuned-wtq",
+)
+
+
 class TFAutoModelForTokenClassification(_BaseAutoModelClass):
     _model_mapping = TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING
 

diff --git a/src/transformers/models/tapas/__init__.py b/src/transformers/models/tapas/__init__.py
@@ -18,7 +18,7 @@
 
 from typing import TYPE_CHECKING
 
-from ...file_utils import _LazyModule, is_torch_available
+from ...file_utils import _LazyModule, is_tf_available, is_torch_available
 
 
 _import_structure = {
@@ -36,6 +36,15 @@
         "TapasPreTrainedModel",
         "load_tf_weights_in_tapas",
     ]
+if is_tf_available():
+    _import_structure["modeling_tf_tapas"] = [
+        "TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST",
+        "TFTapasForMaskedLM",
+        "TFTapasForQuestionAnswering",
+        "TFTapasForSequenceClassification",
+        "TFTapasModel",
+        "TFTapasPreTrainedModel",
+    ]
 
 
 if TYPE_CHECKING:
@@ -53,6 +62,17 @@
             load_tf_weights_in_tapas,
         )
 
+    if is_tf_available():
+        from .modeling_tf_tapas import (
+            TF_TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST,
+            TFTapasForMaskedLM,
+            TFTapasForQuestionAnswering,
+            TFTapasForSequenceClassification,
+            TFTapasModel,
+            TFTapasPreTrainedModel,
+        )
+
+
 else:
     import sys