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Results 21 - 30 of 74 for mat_mul (0.17 sec)
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tensorflow/compiler/mlir/tensorflow/tests/device_assignment_by_func_attr.mlir
// CHECK: device = "xpu" %0 = "tf.Const"() {value = dense<[[1.0, 2.0, 3.0]]> : tensor<1x3xf32>} : () -> tensor<1x3xf32> // CHECK: device = "xpu" %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: Tue May 10 00:30:05 UTC 2022 - 1.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/prepare_quantize_drq.mlir
%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 // CHECK-DAG: %[[CONST:.*]] = arith.constant dense<0.000000e+00> : tensor<2x1024xf32>
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/prepare_quantize_drq_per_channel.mlir
%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 // CHECK-DAG: %[[CONST:.*]] = arith.constant dense<0.000000e+00> : tensor<2x1024xf32>
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/tensorflow/tests/tf_saved_model/basic_v1.py
# CHECK-SAME: attributes {{.*}} tf_saved_model.exported_names = ["key"] # CHECK-NEXT: [[R0:%.*]] = "tf.ReadVariableOp"([[ARG1]]) {{{.*}}} : (tensor<!tf_type.resource<tensor<1x3xf32>>>) -> tensor<1x3xf32> # CHECK-NEXT: [[R1:%.*]] = "tf.MatMul"([[ARG0]], [[R0]]) <{{{.*}}}> {device = ""} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32> # CHECK-NEXT: return [[R1]] : tensor<3x3xf32> def Test(): x = tf.constant([[1.0], [1.0], [1.0]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 08:49:35 UTC 2023 - 2.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/ifrt/sink_variable_as_named_array.mlir
// CHECK: "tf.VarHandleOp" // CHECK-NOT: [[VARIABLE:%.*]] = "tf.ReadVariableOp" // CHECK-NEXT: [[KEY:%.*]], [[FUTURE:%.*]] = "tf.IfrtLoadVariable" // CHECK-SAME: used_by_host = true // CHECK-NEXT: [[MATRES:%.*]] = "tf.MatMul"(%arg0, [[FUTURE]]) // CHECK-NEXT: [[RES:%.*]] = "tf.IfrtCall"(%arg0, [[KEY]]) <{program_id = 6515870160938153680 : i64, variable_arg_indices = [1 : i32]}> // CHECK-NEXT: return [[RES]], [[MATRES]] : tensor<1x1xf32>, tensor<1x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 15:33:17 UTC 2024 - 5.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/include_variables_in_init_v1.py
# CHECK-NEXT: %[[READ_VAR_0:.*]] = "tf.ReadVariableOp"(%[[ARG_2]]) {{{.*}}} : (tensor<!tf_type.resource<tensor<1x3xf32>>>) -> tensor<1x3xf32> # CHECK-NEXT: %[[MATMUL_0:.*]] = "tf.MatMul"(%[[ARG_1]], %[[READ_VAR_0]]) <{{{.*}}}> {{{.*}}} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32> # CHECK-NEXT: return %[[MATMUL_0]] : tensor<3x3xf32> def Test(): x = tf.constant([[1.0], [1.0], [1.0]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 08:49:35 UTC 2023 - 3.7K bytes - Viewed (0) -
tensorflow/cc/framework/cc_ops_test.cc
// It's being used here ONLY to ensure that, that style is tested. MatMul m(root, c, {{41}, {1}}); TF_EXPECT_OK(root.status()); Tensor out; test::GetTensor(root, m, &out); test::ExpectTensorEqual<int>(out, test::AsTensor<int>({42}, {1, 1})); } TEST(CCOpTest, Attrs) { Scope root = Scope::NewRootScope(); auto m = MatMul(root, {{1}, {1}}, {{41}, {1}}, MatMul::TransposeA(true)); TF_EXPECT_OK(root.status()); Tensor out;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 15 15:13:38 UTC 2023 - 8.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/tensorflow/tests/insert_quantized_functions.mlir
// CHECK: func private @quantized_matmul_with_bias_and_relu_fn // CHECK: func private @quantized_matmul_with_bias_and_relu6_fn // CHECK: func private @quantized_matmul_fn // CHECK-SAME: tf_quant.quantized_ops = ["MatMul"] // CHECK: func private @quantized_matmul_with_relu_fn // CHECK: func private @quantized_matmul_with_relu6_fn // CHECK: func private @quantized_conv3d_with_bias_fn // CHECK-SAME: tf_quant.quantized_ops = ["Conv3D", "BiasAdd"]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Aug 29 01:13:58 UTC 2023 - 3.3K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf_saved_model/remove_init_variable_v1.py
# CHECK-SAME: attributes {{.*}} tf_saved_model.exported_names = ["key"] # CHECK-NEXT: [[R0:%.*]] = "tf.ReadVariableOp"([[ARG1]]) {{{.*}}} : (tensor<!tf_type.resource<tensor<1x3xf32>>>) -> tensor<1x3xf32> # CHECK-NEXT: [[R1:%.*]] = "tf.MatMul"([[ARG0]], [[R0]]) <{{{.*}}}> {{{.*}}} : (tensor<3x1xf32>, tensor<1x3xf32>) -> tensor<3x3xf32> # CHECK-NEXT: return [[R1]] : tensor<3x3xf32> def Test(): x = tf.constant([[1.0], [1.0], [1.0]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 31 08:49:35 UTC 2023 - 2.8K bytes - Viewed (0) -
tensorflow/c/experimental/ops/gen/cpp/golden/testing_ops.cc.golden
TF_RETURN_IF_ERROR(op_ptr->AddInput(x)); int num_retvals = 1; return op_ptr->Execute(absl::MakeSpan(y, 1), &num_retvals); } // Op: MatMul() // Summary: // // Description:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Nov 16 19:04:03 UTC 2023 - 6.5K bytes - Viewed (0)