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tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/util.h
// applying the permutation to a given shape through a transpose. PermutationAndShape GetPermutationAndTransposedShape( llvm::ArrayRef<int64_t> permutation_array, ShapedType input_type, ConversionPatternRewriter& rewriter); // Create a single const integer. Value BuildIntConstOp(ImplicitLocOpBuilder& builder, ConversionPatternRewriter& rewriter, int64_t const_value,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Nov 08 11:35:25 UTC 2023 - 6.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/translate/tf_mlir_translate_registration.cc
enable_shape_inference, unconditionally_use_set_output_shapes, enable_soft_placement, set_original_tf_func_name}; auto module_or = tensorflow::GraphdefToMlirTranslateFunction( input, input_arrays, input_dtypes, input_shapes, output_arrays, control_output_arrays, options, context); if (!module_or.status().ok()) return nullptr; return std::move(module_or).value(); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 22:19:26 UTC 2024 - 7.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_model_test.cc
TfLiteStatus QuantizeModel(ModelT* model, const TensorType& input_type, const TensorType& output_type, bool allow_float, std::string& output_buffer) { return QuantizeModel(model, input_type, output_type, allow_float, /*operator_names=*/{}, TensorType_INT8, output_buffer); } TfLiteStatus QuantizeModel(ModelT* model, const TensorType& input_type,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 73.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/prepare_quantize.cc
BoolAttr narrow_range = builder.getBoolAttr(false); auto add_quantize_op = [&](Location loc, Type input_type, Block* block, Block::iterator insertion_point, Value arg, int i) { if (auto shaped = mlir::dyn_cast<ShapedType>(input_type)) { if (mlir::isa<FloatType>(shaped.getElementType())) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 17.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test_base.py
return in_placeholder, output_tensor def _create_simple_tf1_gather_model( self, input_type: dtypes.DType, use_variable_for_filter=False ) -> Tuple[core.Tensor, core.Tensor]: """Creates a basic gather model. This is intended to be used for TF1 (graph mode) tests. Args: input_type: type of the input index tensor for gather operation.
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/compiler/mlir/tensorflow/translate/tf_mlir_translate_cl.h
#include "llvm/Support/CommandLine.h" // Please see the implementation file for documentation of these options. // Import options. extern llvm::cl::opt<std::string> input_arrays; extern llvm::cl::opt<std::string> input_dtypes; extern llvm::cl::opt<std::string> input_shapes; extern llvm::cl::opt<std::string> output_arrays; extern llvm::cl::opt<std::string> control_output_arrays; extern llvm::cl::opt<std::string> inference_type;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Aug 10 20:59:50 UTC 2023 - 2.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/replace_cast_hacks_with_tf_xla_ops.cc
GetBroadcastShapesForBatchMatmul(ShapedType input_type, ShapedType weight_type) { ArrayRef<int64_t> input_shape = input_type.getShape(); ArrayRef<int64_t> weight_shape = weight_type.getShape(); const int64_t num_matmul_dim = 2; const int64_t num_input_batch_dim = input_type.getRank() - num_matmul_dim;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 47.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/merge_save_function_ops_to_main.cc
file_prefix_arg_type, NameLoc::get(builder.getStringAttr(kTfFilePrefix))); SmallVector<Type> input_types(main_func_op.getArgumentTypes()); input_types.emplace_back(file_prefix_arg_type); main_func_op.setType( builder.getFunctionType(input_types, main_func_op.getResultTypes())); // Add "__tf_file_prefix" to the "tf_saved_model.index_path" attribute for the
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfr/integration/tfr_decompose_ctx.cc
DataTypeVector input_dtys, output_dtys; TF_RETURN_IF_ERROR(InputTypesForNode(node_def, *op_def, &input_dtys)); TF_RETURN_IF_ERROR(OutputTypesForNode(node_def, *op_def, &output_dtys)); mlir::MLIRContext* context = tfr_module_.getContext(); llvm::SmallVector<mlir::Type, 4> input_tys, output_tys; mlir::Builder builder(context); for (auto ty : input_dtys) { mlir::Type elt_ty;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 29 02:34:43 UTC 2024 - 9.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test.py
@test_util.run_in_graph_and_eager_modes def test_qat_gather_and_conv_model( self, ): input_type = dtypes.int32 model = self._create_simple_gather_and_conv_model( input_type, filter_shape=(2, 3, 3, 1024), is_qat_model=True, ) saved_model_save.save(model, self._input_saved_model_path)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 03:36:50 UTC 2024 - 235.6K bytes - Viewed (0)