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Results 1 - 10 of 10 for 1x512x4xf32 (0.23 sec)
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tensorflow/compiler/mlir/tf2xla/tests/legalize-tf.mlir
func.func @slice_mhlo_sizes(%arg0: tensor<1x1024x4xf32>, %arg1: tensor<3xi32>) -> tensor<1x512x4xf32> { // CHECK-NOT: "tf.Slice" %0 = "mhlo.constant"() {value = dense<[1, 512, 4]> : tensor<3xi32>} : () -> tensor<3xi32> %1 = "tf.Slice"(%arg0, %arg1, %0) : (tensor<1x1024x4xf32>, tensor<3xi32>, tensor<3xi32>) -> tensor<1x512x4xf32> func.return %1 : tensor<1x512x4xf32> } // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon May 06 18:46:23 UTC 2024 - 335.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/pipelines/process_nchw_tensor.mlir
// CHECK: %[[ADD:.+]] = stablehlo.add %[[CONV]], %[[BIAS_CONST]] : tensor<1x5x5x4xf32> // CHECK: %[[MAX:.+]] = stablehlo.maximum %[[ADD]], %[[ZERO_CONST]] : tensor<1x5x5x4xf32> // CHECK: %[[TRANSPOSE_1:.+]] = stablehlo.transpose %[[MAX]], dims = [0, 3, 1, 2] : (tensor<1x5x5x4xf32>) -> tensor<1x4x5x5xf32> // CHECK: return %[[TRANSPOSE_1]] // -----
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 12.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/defer_activation_transpose.mlir
func.func @add_with_activation_transpose_permutation_mismatch( %arg0: tensor<1x2x3x4xf32>) -> tensor<1x3x2x4xf32> { %0 = stablehlo.constant dense<2.000000e+00> : tensor<1x3x2x4xf32> %1 = stablehlo.transpose %arg0, dims = [0, 2, 1, 3] : (tensor<1x2x3x4xf32>) -> tensor<1x3x2x4xf32> %2 = stablehlo.add %1, %0 : tensor<1x3x2x4xf32> return %2 : tensor<1x3x2x4xf32> } // CHECK: %[[TRANSPOSE_0:.+]] = stablehlo.transpose
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 20:32:46 UTC 2024 - 14.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/tac/tests/device-transform-nnapi.mlir
func.func @mean_4d_no_keepdim(%arg0: tensor<1x48x48x512xf32>) -> tensor<1x512xf32> { %cst = arith.constant dense<[1, 2]> : tensor<2xi32> %0 = "tfl.mean"(%arg0, %cst) {keep_dims = false} : (tensor<1x48x48x512xf32>, tensor<2xi32>) -> tensor<1x512xf32> func.return %0 : tensor<1x512xf32> } // CHECK: func @mean_4d_no_keepdim([[VAL_0:%.*]]: tensor<1x48x48x512xf32>) -> tensor<1x512xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 4.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/common/lift_as_function_call_test.cc
return %0 : tensor<1x1x4xf32> } )mlir"; const OwningOpRef<ModuleOp> module_op = ParseModuleOpString(kXlaCallModuleOpWithQuantizationMethodAttr); ASSERT_TRUE(module_op); func::FuncOp main_fn = FindMainFuncOp(*module_op);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 26.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/tests/tf_to_corert/fallback.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 08 00:18:59 UTC 2024 - 9.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/api/v2/legalize_tf_test.cc
%%arg1 = "tf.Const"() {value = dense<-3.0> : tensor<1x2x4xf32>} : () -> tensor<1x2x4xf32> %%1 = "tf.%s"(%%arg0, %%arg1) {T = f32, adj_x = false, adj_y = false, grad_x = false, grad_y = false, device = ""} : (tensor<1x4x2xf32>, tensor<1x2x4xf32>) -> tensor<1x4x4xf32> func.return %%1 : tensor<1x4x4xf32> } })"; std::string mat_mul_method =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 13 23:59:33 UTC 2024 - 16.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/optimize.mlir
%cst1 = arith.constant dense<[[[2.0, 3.0, 4.0, 5.0]]]> : tensor<1x1x4xf32> %0 = "tfl.fully_connected" (%arg0, %arg1, %cst) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<1x40x37xf32>, tensor<4x37xf32>, none) -> (tensor<1x40x4xf32>) %1 = "tfl.add"(%0, %cst1) {fused_activation_function = "NONE"} : (tensor<1x40x4xf32>, tensor<1x1x4xf32>) -> tensor<1x40x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 20:31:41 UTC 2024 - 284.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/tfl_legalize_hlo.mlir
// CHECK-NEXT: %[[BMM_0:.*]] = "tfl.batch_matmul"(%[[RESHAPED_0]], %[[RESHAPED_1]]) <{adj_x = false, adj_y = false, asymmetric_quantize_inputs = false}> : (tensor<3x5x12xf32>, tensor<3x12x4xf32>) -> tensor<3x5x4xf32> // CHECK-NEXT: %[[RESHAPED_BMM:.*]] = mhlo.reshape %[[BMM_0]] // CHECK-NEXT: return %[[RESHAPED_BMM]] : tensor<3x5x1x4xf32> }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 40.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/legalize_hlo.mlir
// CHECK: %[[VAL_9:.*]] = "tf.Reshape"(%[[VAL_5]], %[[VAL_8]]) : (tensor<3x2x6x4xf32>, tensor<3xi64>) -> tensor<3x12x4xf32> // CHECK: %[[VAL_10:.*]] = "tf.BatchMatMulV3"(%[[VAL_7]], %[[VAL_9]]) <{adj_x = false, adj_y = false, grad_x = false, grad_y = false}> : (tensor<3x5x12xf32>, tensor<3x12x4xf32>) -> tensor<3x5x4xf32> // CHECK: %[[VAL_11:.*]] = arith.constant dense<[3, 5, 1, 4]> : tensor<4xi64>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed May 29 07:26:59 UTC 2024 - 340.2K bytes - Viewed (0)