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Results 71 - 80 of 137 for matmul_0 (0.51 sec)
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tensorflow/c/eager/c_api_remote_test_util.h
==============================================================================*/ #ifndef TENSORFLOW_C_EAGER_C_API_REMOTE_TEST_UTIL_H_ #define TENSORFLOW_C_EAGER_C_API_REMOTE_TEST_UTIL_H_ // Run a function containing a MatMul op and check its output. // If heavy_load_on_streaming_rpc is true, send some rpc requests before the one // which creates a remote input, to simulate a scenario that the remote input
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Dec 11 22:56:03 UTC 2020 - 1.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/device_assignment.mlir
func.func @device_test(%arg0: tensor<3x1xf32>) -> (tensor<3x3xf32>) { // CHECK: device = "gpu" %0 = "tf.Const"() {value = dense<[[1.0, 2.0, 3.0]]> : tensor<1x3xf32>} : () -> tensor<1x3xf32> // CHECK: device = "gpu" %1 = "tf.MatMul"(%arg0, %0) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"], device = "", transpose_a = false, transpose_b = false} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32> // CHECK: device = "cpu"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 24 05:47:26 UTC 2022 - 924 bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/insert_quantized_functions_drq.mlir
// CHECK-NOT: func private @internal_quantize_i8 // CHECK-NOT: func private @internal_matmul_fn // CHECK: func private @quantized_matmul_fn // CHECK-SAME: tf_quant.quantized_ops = ["MatMul"] // CHECK: func private @quantized_conv2d_fn // CHECK-SAME: tf_quant.quantized_ops = ["Conv2D"] // CHECK: func private @quantized_depthwise_conv2d_fn // CHECK-SAME: tf_quant.quantized_ops = ["DepthwiseConv2D"]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Dec 01 12:06:54 UTC 2022 - 1K bytes - Viewed (0) -
tensorflow/compiler/jit/tests/keras_imagenet_main.golden_summary
ArgMax 1 AssignAddVariableOp 1 BiasAdd 1 BiasAddGrad 1 Cast 115 Const 407 Conv2D 53 Conv2DBackpropFilter 53 Conv2DBackpropInput 52 Equal 1 FusedBatchNormGradV2 53 FusedBatchNormV2 53 MatMul 3 MaxPool 1 MaxPoolGrad 1 Mean 1 Mul 218 Pad 2 ReadVariableOp 538 Relu 49 ReluGrad 49 Reshape 2 ResourceApplyKerasMomentum 161 Slice 1 Softmax 1
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 06 10:38:14 UTC 2023 - 874 bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/quantization/tensorflow/fallback_to_flex_ops.cc
TF::DepthwiseConv2dNativeOp::getOperationName().str(), TF::FusedBatchNormV3Op::getOperationName().str(), TF::GatherV2Op::getOperationName().str(), TF::MatMulOp::getOperationName().str(), TF::MaxPoolOp::getOperationName().str(), TF::MaximumOp::getOperationName().str(), TF::MeanOp::getOperationName().str(),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 12.2K bytes - Viewed (0) -
tensorflow/c/experimental/ops/gen/cpp/cpp_generator_test.cc
string output_dir = "tensorflow/c/experimental/ops/gen/cpp/golden"; string source_dir = "tensorflow"; string api_dirs = ""; std::vector<string> ops = { "Neg", // Simple unary Op "MatMul", // 2 inputs & attrs with default values "IdentityN", // Variadic input+output "SparseSoftmaxCrossEntropyWithLogits", // 2 outputs "AccumulatorApplyGradient", // 0 outputs
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 18 17:02:28 UTC 2022 - 2.9K bytes - Viewed (0) -
tensorflow/c/experimental/ops/gen/cpp/golden/testing_ops.h.golden
namespace tensorflow { namespace ops { // Status Neg(AbstractContext* ctx, AbstractTensorHandle* const x, AbstractTensorHandle** y, const char* name = nullptr, const char* raw_device_name = nullptr); //
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Nov 16 19:04:03 UTC 2023 - 2.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/legalize_hlo_conversions/dot_general.cc
auto matmul = rewriter.create<TFL::BatchMatMulOp>( loc, RankedTensorType::get(matmul_shape, result_type.getElementType()), lhs_flattend, rhs_flattend, /*adj_x*/ false_attr, /*adj_y*/ false_attr, /*asym_quant_input*/ false_attr); if (result_type.hasStaticShape()) { auto reshaped = rewriter.create<mhlo::ReshapeOp>(loc, result_type, matmul.getResult()); return reshaped.getResult();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 19.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/passes/quantized_function_library_xla_weight_only.mlir
// Use identity op to avoid the filter being constant-folded. %identity = "tf.Identity"(%filter) : (tensor<*xi8>) -> tensor<*xi8> %2 = "tf.Cast"(%identity) {Truncate = false} : (tensor<*xi8>) -> tensor<*xf32> %3 = "tf.MatMul"(%input, %2) { attr_map = "transpose_a:0,transpose_b:1" } : (tensor<*xf32>, tensor<*xf32>) -> tensor<*xf32> func.return %3 : tensor<*xf32> } func.func private @internal_conv2d_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/tensorflow/tests/batchmatmul_to_einsum.mlir
// RUN: tf-opt %s -tf-batch-matmul-to-tf-einsum | FileCheck %s func.func @test_batch_matmul_to_einsum(%arg0: tensor<1x2x3xf32>, %arg1: tensor<3x4xf32>) -> tensor<1x2x4xf32> { // CHECK-LABEL: test_batch_matmul_to_einsum // CHECK: "tf.Einsum"(%arg0, %arg1) <{equation = "...mk,...kn->...mn"}> : (tensor<1x2x3xf32>, tensor<3x4xf32>) -> tensor<1x2x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 3K bytes - Viewed (0)