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Results 51 - 60 of 76 for conv2 (0.24 sec)
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tensorflow/compiler/mlir/lite/tests/prepare-tf-fake-quant.mlir
// CHECK: %[[DEQUANTIZE:.*]] = "tfl.dequantize"(%[[QUANTIZE]]) // CHECK: %[[CONV:.*]] = "tfl.conv_2d"(%arg0, %[[DEQUANTIZE]], %[[CONSTANT]]) // CHECK: return %[[CONV]] } // CHECK-LABEL: perChannelFakeQuantWithConv2D func.func @perChannelFakeQuantWithConv2D(tensor<256x32x32x3xf32>) -> (tensor<256x8x7x16xf32>) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 20.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/insert_calibration_statistics_saver.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 01:09:50 UTC 2024 - 24.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/passes/insert_weight_param.cc
const auto module_op = op->getParentOfType<ModuleOp>(); const SymbolTable symbol_table(module_op); func::FuncOp func = symbol_table.lookup<func::FuncOp>(function_name); if (function_name.contains("conv")) { return (*(func.getOps<mlir::stablehlo::ConvolutionOp>().begin())) .getDimensionNumbers() .getKernelOutputFeatureDimension(); } else if (function_name.contains("dot_general")) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 05:56:10 UTC 2024 - 10.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test.py
), ) quantization.quantize_saved_model( self._input_saved_model_path, self._output_saved_model_path, config, ) expected_outputs = model.conv2d(input_data) root = load.load(self._output_saved_model_path) self.assertCountEqual(root.signatures.keys(), {'serving_default'}) new_outputs = root.signatures['serving_default'](
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/common/attrs_and_constraints.h
// or `std::nullopt` if the given op is not per-channel quantizable. std::optional<int64_t> GetDotGeneralQuantizationDim( ::mlir::stablehlo::DotGeneralOp dot_general_op); // Checks if a `StringRef` contains 'conv' or 'dot_general'. bool ContainsConvOrDot(StringRef str); } // namespace mlir::quant
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 9.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/canonicalize.mlir
%con12 = "tf.Const"() { value = dense<[3.0, 4.0]> : tensor<2xf32> } : () -> tensor<2xf32> %con21 = "tf.Const"() { value = dense<[0.0, 2.0]> : tensor<2xf32> } : () -> tensor<2xf32> %con22 = "tf.Const"() { value = dense<[0.0, 0.0]> : tensor<2xf32> } : () -> tensor<2xf32> %con31 = "tf.Const"() { value = dense<[0.0, 0.0]> : tensor<2xf32> } : () -> tensor<2xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 09 22:07:10 UTC 2024 - 132.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/lite/quantize_weights_test.cc
const auto float_graph = model_->subgraphs()->Get(subgraph_idx); ASSERT_EQ(quantized_graph->tensors()->size(), float_graph->tensors()->size()); // Make sure the graph only has one Conv operation. ASSERT_EQ(quantized_graph->operators()->size(), 1); const auto op = quantized_graph->operators()->Get(0); const uint32_t op_code_idx = op->opcode_index();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jun 12 23:15:24 UTC 2024 - 32.3K bytes - Viewed (0) -
platforms/software/dependency-management/src/test/groovy/org/gradle/api/internal/artifacts/configurations/DefaultConfigurationSpec.groovy
def "reports indirect cycle in extended configurations"() { def configuration = conf() def conf1 = conf("other") def conf2 = conf("other2") when: configuration.extendsFrom(conf1) conf1.extendsFrom(conf2) conf2.extendsFrom(configuration) then: thrown InvalidUserDataException } def "reports cycle introduced by setExtends"() {
Registered: Wed Jun 12 18:38:38 UTC 2024 - Last Modified: Thu May 23 17:30:13 UTC 2024 - 64.8K bytes - Viewed (0) -
src/cmd/cgo/gcc.go
conv.getTypeIDs[n.Go[:len(n.Go)-9]] = true } } for i, n := range names { if types[i] == nil { continue } pos := f.NamePos[n] f, fok := types[i].(*dwarf.FuncType) if n.Kind != "type" && fok { n.Kind = "func" n.FuncType = conv.FuncType(f, pos) } else { n.Type = conv.Type(types[i], pos) switch n.Kind { case "iconst":
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon May 20 15:50:06 UTC 2024 - 97K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/transforms/legalize_tf.cc
}; using ConvertConv2DDynamic = ConvertConvDynamic<TF::Conv2DOp, /*num_spatial_dims=*/2>; // Converts the TensorFlow conv op in template to the generic HLO conv op by // converting TensorFlow op attributes to HLO op attributes. // // Sample result for Conv2D: // // %conv = "mhlo.convolution"(%input, %filter) { // strides = [1, 2], // paddings = [[1, 0], [1, 1]], // ... // } //
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Jun 11 20:00:43 UTC 2024 - 291.8K bytes - Viewed (0)