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Results 1 - 10 of 13 for bias_shape (0.34 sec)
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tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test_base.py
x_shape = [label_to_size.get(x_label) for x_label in x_labels] y_shape = [label_to_size.get(y_label) for y_label in y_labels] bias_shape = None if use_bias: bias_shape = [label_to_size.get(out_label) for out_label in out_labels] bias_shape = bias_shape[-1:] contracting_dims = set() x_signature = list(x_shape) y_signature = list(y_shape) if generate_unknown_shape_signature:
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/compiler/mlir/lite/utils/lstm_utils_test.cc
SmallVector<int64_t, 1> bias_shape{2}; SmallVector<int64_t, 2> projection_shape{1, 2}; SmallVector<int64_t, 1> layer_norm_scale{4}; SmallVector<int64_t, 2> output_shape{1, 2}; auto input_type = RankedTensorType::get(input_shape, builder->getF32Type()); auto weight_type = RankedTensorType::get(weight_shape, builder->getF32Type()); auto bias_type = RankedTensorType::get(bias_shape, builder->getF32Type());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test_base.py
x_shape = [label_to_size.get(x_label) for x_label in x_labels] y_shape = [label_to_size.get(y_label) for y_label in y_labels] bias_shape = None if use_bias: bias_shape = [label_to_size.get(out_label) for out_label in out_labels] bias_shape = bias_shape[-1:] contracting_dims = set() x_signature = list(x_shape) y_signature = list(y_shape)
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/gradients/nn_grad_test.cc
} TEST_F(NNGradTest, BiasAddGradHelper) { TensorShape shape({4, 5}); TensorShape bias_shape({5}); auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(shape)); auto bias = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(bias_shape)); auto y = BiasAdd(scope_, x, bias); RunTest({x, bias}, {shape, bias_shape}, {y}, {shape}); } TEST_F(NNGradTest, Conv2DGrad) { TensorShape shape({1, 2, 2, 1});
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 22 20:45:22 UTC 2022 - 15K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test.py
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/lite/stablehlo/transforms/uniform_quantized_stablehlo_to_tfl_pass.cc
filter_quantized_element_type.getZeroPoint()); } SmallVector<int64_t, 1> bias_shape = {filter_shape[0]}; auto bias_type = RankedTensorType::getChecked(loc, bias_shape, bias_quantized_type); auto bias_value_type = RankedTensorType::getChecked( loc, std::move(bias_shape), rewriter.getI32Type()); auto bias_value = DenseIntElementsAttr::get(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Apr 22 09:00:19 UTC 2024 - 99.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test.py
self, equation: str, ): _, y_shape, bias_shape, x_signature, y_signature = ( self._prepare_sample_einsum_datashapes(equation, use_bias=True) ) model = self._create_einsum_model( self._input_saved_model_path, equation, y_shape, x_signature, y_signature, bias_shape, ) # Generate model input data.
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/passes/quantized_function_library_uniform_quantized.mlir
%input_scale : tensor<*xf32>, %input_zp : tensor<*xi32>, %filter_scale : tensor<*xf32>, %filter_zp : tensor<*xi32>, %bias_scale : tensor<*xf32>, %bias_zp : tensor<*xi32>, %out_scale : tensor<*xf32>, %out_zp : tensor<*xi32>) -> tensor<*x${output_type}> attributes {tf_quant.quantized_ops = ${quantized_ops}} {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Aug 29 01:13:58 UTC 2023 - 19.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/quantization_lib/quantization_driver.cc
Operation* op, const int bias_index, const ArrayRef<int> non_bias_operand_indices, const AccumulatorScaleFunc func) { QuantState& bias_state = GetOperandQuantState(op, bias_index); if (!bias_state.IsEmpty()) { return bias_state.params; } std::vector<QuantizedType> op_types{}; op_types.reserve(non_bias_operand_indices.size()); int adjusted_quant_dim = -1;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 38.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library.mlir
%input_scale : tensor<*xf32>, %input_zp : tensor<*xi32>, %filter_scale : tensor<*xf32>, %filter_zp : tensor<*xi32>, %bias_scale : tensor<*xf32>, %bias_zp : tensor<*xi32>, %out_scale : tensor<*xf32>, %out_zp : tensor<*xi32>) -> tensor<*x${output_type}> attributes {tf_quant.quantized_ops = ${quantized_ops}} {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Jan 08 01:16:10 UTC 2024 - 30.6K bytes - Viewed (0)