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Results 11 - 20 of 61 for mat_mul (0.17 sec)
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tensorflow/c/experimental/gradients/math_grad.cc
std::string name_grad_B = "MatMul_Grad_B"; if (!t_a && !t_b) { TF_RETURN_IF_ERROR(MatMul(ctx, upstream_grad, B.get(), &matmul_A_output, /*transpose_a = */ false, /*transpose_b = */ true, name_grad_A.c_str())); TF_RETURN_IF_ERROR(MatMul(ctx, A.get(), upstream_grad, &matmul_B_output, /*transpose_a = */ true,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 28 13:53:47 UTC 2024 - 15.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_weight_only.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 11.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/mlrt/async_while.mlir
%out_matrix = "tf.MatMul"(%in_matrix, %matrix) : (tensor<3x3xf32>, tensor<3x3xf32>) -> tensor<3x3xf32> %in_matrix1 = "tf.TensorArrayReadV3"(%handle_2, %loop_count, %flow_in_2) : (tensor<?x!tf_type.resource>, tensor<i32>, tensor<*xf32>) -> tensor<3x3xf32> %out_matrix1 = "tf.MatMul"(%out_matrix, %matrix_2) : (tensor<3x3xf32>, tensor<3x3xf32>) -> tensor<3x3xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 22.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test_base.py
out = math_ops.matmul(input_tensor, self.filters, name='sample/matmul') if bias_fn is not None: out = bias_fn(out, self.bias) if activation_fn is not None: out = activation_fn(out) return {'output': out} model = MatmulModel(weight_shape) saved_model_save.save( model, saved_model_path, signatures=model.matmul.get_concrete_function(
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/quantization/tensorflow/tests/lift_quantizable_spots_as_functions.mlir
// CHECK-LABEL: private @composite_matmul_with_bias_and_relu6_fn_1 // CHECK-NEXT: %[[matmul:.*]] = "tf.MatMul"(%arg0, %arg1) // CHECK-SAME: attr_map = "0:transpose_a,1:transpose_b" // CHECK-NEXT: tf.BiasAdd // CHECK-NEXT: tf.Relu6 // CHECK-NEXT: return // CHECK-LABEL: private @composite_matmul_with_bias_and_relu_fn_1 // CHECK-NEXT: tf.MatMul"(%arg0, %arg1) // CHECK-SAME: attr_map = "0:transpose_a,1:transpose_b"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 26.5K bytes - Viewed (0) -
tensorflow/c/experimental/gradients/math_grad_test.cc
absl::Span<AbstractTensorHandle* const> inputs, absl::Span<AbstractTensorHandle*> outputs) -> Status { return ops::MatMul(ctx, inputs[0], inputs[1], &outputs[0], transpose_a, transpose_b, "MatMul"); }; ASSERT_NO_FATAL_FAILURE(CompareNumericalAndAutodiffGradients( MatMulModel, BuildGradModel(MatMulModel, registry_),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 13 17:32:14 UTC 2023 - 16.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/quantize_composite_functions_drq.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jan 05 18:35:42 UTC 2024 - 9.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/lift_quantizable_spots_as_functions_drq.mlir
%cst = "tf.Const"() {value = dense<0.000000e+00> : tensor<512x512xf32>} : () -> tensor<512x512xf32> %out_1 = "tf.MatMul"(%arg0, %cst) { device = "", transpose_a = false, transpose_b = false } : (tensor<1x12x12x512xf32>, tensor<512x512xf32>) -> tensor<*xf32> %out_2 = "tf.MatMul"(%arg0, %arg0) { device = "", transpose_a = false, transpose_b = true } : (tensor<1x12x12x512xf32>, tensor<1x12x12x512xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 11.8K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/transforms/prepare_patterns.td
(TF_SubOp $beta, (TF_MulOp $m, $mul)))>; class TFi32<int v> : ConstantAttr<I32ElementsAttr, !cast<string>(v)>; // Matmul without transpose on b to matmul with explicit transpose op and // transposed b. def ConvertMatmulWithoutTransposeToWithTranspose : Pat<(TF_MatMulOp $a, $b, ConstBoolAttrFalse:$at, ConstBoolAttrFalse, $grad_a, $grad_b),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 10.5K 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)