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Results 1 - 10 of 11 for get_concrete_function (0.24 sec)
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tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test_base.py
return {'output': out} model = MatmulModel(weight_shape) saved_model_save.save( model, saved_model_path, signatures=model.matmul.get_concrete_function( tensor_spec.TensorSpec( shape=input_shape, dtype=dtypes.float32, name='input_tensor' ) ), ) return model def _any_log_contains(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 18.2K bytes - Viewed (0) -
tensorflow/cc/saved_model/testdata/generate_chunked_models.py
root = module.Module() root.c = constant_op.constant(np.random.random_sample([150, 150])) constants.debug_set_max_size(80000) root.get_c = def_function.function(lambda: root.c) signatures = root.get_c.get_concrete_function() save.save(root, non_chunked_dir, signatures=signatures, options=save_options.SaveOptions(experimental_image_format=False)) def generate_chunked_model(non_chunked_dir: str, chunked_dir: str):
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 08 21:43:11 UTC 2023 - 2.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/debuginfo/concrete_function_error.py
@tf.function( input_signature=[tf.TensorSpec(shape=[3, 3], dtype=tf.float32)]) def model(x): y = tf.math.betainc(x, 0.5, 1.0) # Not supported return y + y func = model.get_concrete_function() converter = tf.lite.TFLiteConverter.from_concrete_functions([func], model) converter.convert() # pylint: disable=line-too-long # CHECK-LABEL: testConcreteFunctionDebugInfo
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Sep 28 21:37:05 UTC 2021 - 2.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/concurrency_test.py
), } root = ModelWithAdd() temp_path = self.create_tempdir().full_path saved_model_save.save( root, temp_path, signatures=root.add.get_concrete_function() ) quantization_options = quant_opts_pb2.QuantizationOptions( quantization_method=quant_opts_pb2.QuantizationMethod(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Sep 11 00:47:05 UTC 2023 - 3.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test.py
# Create and save a model having 2 signatures. model = MultipleSignatureModel() signatures = { 'sig1': model.matmul.get_concrete_function( tensor_spec.TensorSpec(shape=(1, 4), dtype=dtypes.float32) ), 'sig2': model.conv.get_concrete_function( tensor_spec.TensorSpec(shape=(1, 3, 4, 3), dtype=dtypes.float32) ), } saved_model_save.save(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 235.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test.py
return {'output': out} model = TwoMatmulModel() input_shape = (1, 2) save.save( model, self._input_saved_model_path, signatures=model.matmul.get_concrete_function( tensor_spec.TensorSpec( shape=input_shape, dtype=dtypes.float32, name='input_tensor' ) ), ) def data_gen() -> repr_dataset.RepresentativeDataset:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 51.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test_base.py
model = MatmulModel(weight_shape, bias_size, activation_fn) saved_model_save.save( model, saved_model_path, signatures=model.matmul.get_concrete_function( tensor_spec.TensorSpec( shape=input_shape, dtype=dtypes.float32, name='input_tensor' ) ), ) return model
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 21 08:51:46 UTC 2024 - 51.2K bytes - Viewed (0) -
tensorflow/cc/experimental/libtf/function.h
private: struct ConcreteFunction { tensorflow::AbstractFunctionPtr trace; TaggedValue input_signature; TaggedValue output_signature; }; tensorflow::StatusOr<ConcreteFunction> GetConcreteFunction(TaggedValue) const; std::vector<ConcreteFunction> concrete_fns_; }; } // namespace libtf } // namespace tf
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Aug 30 21:44:45 UTC 2022 - 1.9K bytes - Viewed (0) -
tensorflow/cc/experimental/libtf/function.cc
StatusOr<TaggedValue> Function::Execute(AbstractContext* ctx, TaggedValue value) const { TF_RETURN_IF_ERROR(VerifySupportedArgs(value)); TF_ASSIGN_OR_RETURN(auto concrete_fn, GetConcreteFunction(value)); std::vector<AbstractTensorHandle*> args; Flatten(value, &args); std::vector<AbstractTensorHandle*> outs( GetFlatSize(concrete_fn.output_signature)); TF_RETURN_IF_ERROR(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 04 19:49:06 UTC 2024 - 9.1K bytes - Viewed (0) -
RELEASE.md
sometimes incorrectly ignored. * functions returned by the `get_concrete_function` method of `tf.function` objects can now be called with arguments consistent with the original arguments or type specs passed to `get_concrete_function`. This calling convention is now the preferred way to use concrete
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 23:24:08 UTC 2024 - 730.3K bytes - Viewed (0)