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Results 1 - 10 of 37 for attr_val (0.11 sec)
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tensorflow/c/experimental/ops/gen/cpp/views/attr_view.cc
string AttrView::DefaultValue() const { const AttrValue &attr_value = attr_.default_value(); switch (attr_value.value_case()) { case AttrValue::VALUE_NOT_SET: return ""; case AttrValue::kType: return DataType_Name(attr_value.type()); case AttrValue::kS: return "\"" + attr_value.s() + "\""; case AttrValue::kI: return std::to_string(attr_value.i()); case AttrValue::kF:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Jun 03 07:02:00 UTC 2024 - 4.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library_uniform_quantized_drq.mlir
// Internal functions should be marked as private. They will be inlined and // deleted in `InsertQuantizedFunctionsPass`. // // For Uniform Quantized op case, attributes are generated during quantize // composite pass. Therefore, attr_map is set to an empty string. module { // Currently only 4-d case is supported func.func @quantized_conv2d_fn( %input : tensor<*xf32>, %weight : tensor<*x!tf_type.qint8>,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Dec 01 12:06:54 UTC 2022 - 3.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library_xla_weight_only.mlir
%2 = "tf.Cast"(%identity) {Truncate = false} : (tensor<*xi8>) -> tensor<*xf32> %3 = "tf.Conv3D"(%input, %2) { padding = "VALID", strides = [1, 1, 1, 1, 1], attr_map = "strides:0,padding:1,dilations:2" } : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32> func.return %3 : tensor<*xf32> } func.func private @internal_batch_matmul_fn(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 03 15:43:38 UTC 2023 - 7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_xla.mlir
// CHECK-SAME: <{data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 2, 2, 1]}> // Check that the `attr_map` attribute has been removed. // CHECK-NOT: attr_map // ----- func.func @conv_with_non_constant_filter(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x2xf32>) -> tensor<*xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 8.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_drq_per_channel.mlir
func.return %1: tensor<*xf32> } func.func private @composite_matmul_fn(%arg0: tensor<1x2x2x3xf32>, %arg1: tensor<2x1024xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} { %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_a", device = "", transpose_a = false, transpose_b = false} : (tensor<1x2x2x3xf32>, tensor<2x1024xf32>) -> tensor<*xf32> return %0 : tensor<*xf32> } // CHECK-LABEL: func @matmul
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 6.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_drq.mlir
func.return %1: tensor<*xf32> } func.func private @composite_matmul_fn(%arg0: tensor<1x2x2x3xf32>, %arg1: tensor<2x1024xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} { %0 = "tf.MatMul"(%arg0, %arg1) {attr_map = "0:transpose_a,1:transpose_a", device = "", transpose_a = false, transpose_b = false} : (tensor<1x2x2x3xf32>, tensor<2x1024xf32>) -> tensor<*xf32> return %0 : tensor<*xf32> } // CHECK-LABEL: func @matmul
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 6.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/preprocess_op_weight_only.mlir
} func.func private @composite_depthwise_conv2d_fn(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x2xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} { %0 = "tf.DepthwiseConv2dNative"(%arg0, %arg1) { attr_map = "0:strides,1:padding,2:explicit_paddings,3:dilations", data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 4.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/preprocess_op.mlir
} func.func private @composite_depthwise_conv2d_fn(%arg0: tensor<1x3x4x3xf32>, %arg1: tensor<2x3x3x2xf32>) -> tensor<*xf32> attributes {tf_quant.composite_function} { %0 = "tf.DepthwiseConv2dNative"(%arg0, %arg1) { attr_map = "0:strides,1:padding,2:explicit_paddings,3:dilations", data_format = "NHWC", device = "", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 2, 1]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/ir/tf_ops_layout_helper.h
(*op)->setAttr("data_format", StringAttr::get(context, target_data_format)); for (auto pair : shuffle_attrs) { StringRef attr_name = pair.first; ArrayAttr attr_value = pair.second; (*op)->setAttr(attr_name, ShuffleArrayAttr(attr_value, reverse_permutation)); } auto fold = cast<FoldOperandsTransposeInterface>(op->getOperation()); for (unsigned idx : fold.GetLayoutDependentResults()) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 08 01:19:25 UTC 2023 - 5.3K bytes - Viewed (0) -
tensorflow/cc/framework/cc_op_gen_util.h
#define TENSORFLOW_CC_FRAMEWORK_CC_OP_GEN_UTIL_H_ #include <string> #include <unordered_map> #include <utility> #include <vector> #include "tensorflow/core/framework/api_def.pb.h" #include "tensorflow/core/framework/attr_value.pb.h" #include "tensorflow/core/framework/attr_value_util.h" #include "tensorflow/core/framework/op_def_util.h" #include "tensorflow/core/framework/op_gen_lib.h" #include "tensorflow/core/framework/tensor.pb.h"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Feb 26 00:57:05 UTC 2024 - 4.6K bytes - Viewed (0)