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tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_xla_selective_quantization.mlir
%cst_0 = "tf.Const"() {value = dense<[-1, 10]> : tensor<2xi32>} : () -> tensor<2xi32> %1 = "tf.MatMul"(%arg0, %arg1) { transpose_a = false, transpose_b = false } : (tensor<1x10xf32>, tensor<10x10xf32>) -> tensor<1x10xf32> loc(fused["MatMul:", "test_opt_out"]) %2 = "tf.Reshape"(%1, %cst_0) : (tensor<1x10xf32>, tensor<2xi32>) -> tensor<?x10xf32> loc(fused["Reshape:", "model/reshape"])
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/c/experimental/ops/math_ops.cc
// outer dimension of "b" (after being transposed if transposed_b is // true). // // *Note*: The default kernel implementation for MatMul on GPUs uses // cublas. Status MatMul(AbstractContext* ctx, AbstractTensorHandle* const a, AbstractTensorHandle* const b, AbstractTensorHandle** product, bool transpose_a, bool transpose_b, const char* name, const char* raw_device_name) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 10 19:11:36 UTC 2022 - 12.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/cast_bf16_ops_to_f32.mlir
} // CHECK: func @cast_bf16_matmul_to_fp32 // CHECK-DAG: %[[cst:.*]] = "tf.Const"() <{value = dense<{{.*}}> : tensor<10x2xf32>}> : () -> tensor<10x2xf32> // CHECK: %[[matmul:.*]] = "tf.MatMul"(%arg0, %[[cst]]) // CHECK: %[[identity:.*]] = "tf.IdentityN"(%[[matmul]]) // CHECK: return %[[identity]] : tensor<1x2xf32> func.func @cast_bf16_depthwise_conv_to_fp32(%arg0: tensor<1x3x4x3xf32>) -> (tensor<1x2x2x6xf32>) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 8.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/ifrt/rewrite_cluster_to_ifrt_call.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Feb 17 07:28:40 UTC 2024 - 9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test.py
] ) def matmul(self, matmul_input: core.Tensor) -> Mapping[str, core.Tensor]: """Performs a matrix multiplication. Args: matmul_input: Input tensor to matmul with the filter. Returns: A map of: output key -> output result. """ out = math_ops.matmul(matmul_input, self.matmul_filters) return {'output': out}
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/tfrt/tests/saved_model/testdata/test.mlir
tf_saved_model.exported_names = ["serving_default"] } { %0 = "tf.ReadVariableOp"(%arg1) {device = ""} : (tensor<!tf_type.resource<tensor<3x1xi32>>>) -> tensor<3x1xi32> %1 = "tf.MatMul"(%arg0, %0) {device = "", transpose_a = false, transpose_b = false} : (tensor<1x3xi32>, tensor<3x1xi32>) -> tensor<1x1xi32> func.return %1 : tensor<1x1xi32> } func.func @predict(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 25 11:03:04 UTC 2022 - 1.6K bytes - Viewed (0) -
tensorflow/c/eager/c_api_unified_experimental_test.cc
EXPECT_EQ(*result_value, 4.0); TF_DeleteTensor(result_tensor); TF_DeleteAbstractTensor(result); TF_DeleteOutputList(o); TF_DeleteExecutionContext(ctx); } // MatMul Test TEST_P(UnifiedCAPI, TestBasicEagerMatMul) { std::unique_ptr<TF_Status, decltype(&TF_DeleteStatus)> status( TF_NewStatus(), TF_DeleteStatus); TFE_ContextOptions* opts = TFE_NewContextOptions();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 19 21:44:52 UTC 2023 - 39.1K bytes - Viewed (0) -
tensorflow/c/experimental/ops/update_cpp_ops.sh
${generate} \ --category=array \ Identity \ IdentityN \ ZerosLike \ Shape \ ExpandDims \ OnesLike ${generate} \ --category=math \ Mul \ Conj \ AddV2 \ MatMul \ Neg \ Sum \ Sub \ Div \ DivNoNan \ Exp \ Sqrt \ SqrtGrad \ Log1p ${generate} \ --category=nn \ SparseSoftmaxCrossEntropyWithLogits \ ReluGrad \ Relu \
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 17 17:54:34 UTC 2022 - 1.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/runtime_fallback/runtime_fallback_ops.td
TFRT attributes are sorted alphabetically, passed in as positional attributes to the TFRT kernel, rather than as named attributes. Example: To run "tf.MatMul" op, which has two boolean attributes, 1. Set _name = "MatMul" 2. For each TF attribute, split it into two attributes, one for name of the TF attribute, and the other for the type and value of the
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 23 19:35:12 UTC 2023 - 5.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test_base.py
@def_function.function def matmul(self, input_tensor: core.Tensor) -> Mapping[str, core.Tensor]: """Performs a matrix multiplication. Depending on self.has_bias and self.activation_fn, it may add a bias term or go through the activaction function. Args: input_tensor: Input tensor to matmul with the filter. Returns:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 21 08:51:46 UTC 2024 - 51.2K bytes - Viewed (0)