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Results 1 - 10 of 28 for 1x4x8x8xf32 (0.15 sec)
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tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/defer_activation_transpose.mlir
%0 = stablehlo.constant dense<2.000000e+00> : tensor<1x4x3x3xf32> %1 = stablehlo.transpose %arg0, dims = [0, 3, 1, 2] : (tensor<1x3x3x4xf32>) -> tensor<1x4x3x3xf32> %2 = stablehlo.add %1, %0 : tensor<1x4x3x3xf32> return %2 : tensor<1x4x3x3xf32> } // CHECK-SAME: (%[[ARG_0:.+]]: tensor<1x3x3x4xf32>) -> tensor<1x4x3x3xf32> // CHECK-DAG: %[[CONST_0:.+]] = stablehlo.constant
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/tensorflow/tests/layout_optimization_move_transposes_end.mlir
func.func @move_across_double_transpose(%arg0: tensor<1x4x4x8xf32>, %arg1: tensor<1x4x4x8xf32>) -> tensor<1x4x8x4xf32> { // CHECK: %[[RES_PERM:.*]] = "tf.Const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi32>}> // CHECK: %[[ADD:[0-9]*]] = "tf.AddV2"(%arg0, %arg1) : (tensor<1x4x4x8xf32>, tensor<1x4x4x8xf32>) -> tensor<1x4x4x8xf32> // CHECK: %[[RES_TRANSPOSE_0:[0-9]*]] = "tf.Transpose"(%[[ADD]], %[[RES_PERM]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/pipelines/process_nchw_tensor.mlir
// CHECK: %[[TRANSPOSE_1:.+]] = stablehlo.transpose %[[CONV]], dims = [0, 3, 1, 2] : (tensor<1x4x4x8xf32>) -> tensor<1x8x4x4xf32> // CHECK: return %[[TRANSPOSE_1]] // ----- // Tests that a `add(convolution(%activation, %weight), %bias)` with the // activation tensor of NCHW format is converted to NHWC convolution + add
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/lite/stablehlo/tests/composite-lowering.mlir
return %2 : tensor<1x1x1x4xf32> } func.func private @XlaCallModule_aten.avg_pool2d.default.impl_2(%arg0: tensor<1x1x1x8xf32>) -> tensor<1x1x1x4xf32> // CHECK-LABEL: avg_pool2d_3 // CHECK: %cst = arith.constant dense<[0, 2, 3, 1]> : tensor<4xi32> // CHECK: %0 = "tfl.transpose"(%arg0, %cst) : (tensor<1x1x1x8xf32>, tensor<4xi32>) -> tensor<1x1x8x1xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Jun 06 18:45:51 UTC 2024 - 32.6K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/components/pre_calibration_component.mlir
// CHECK: %[[CUSTOM_AGGREGATOR_1:.+]], {{.*}}, {{.*}}, {{.*}} = "tf.CustomAggregator"(%[[XLA_CALL_MODULE]]) {{.*}} : (tensor<1x4x4x8xf32>) -> (tensor<1x4x4x8xf32>, tensor<f32>, tensor<f32>, tensor<0xi64>) // CHECK: %[[TRANSPOSE_2:.+]] = stablehlo.transpose %[[CUSTOM_AGGREGATOR_1]], dims = [0, 3, 1, 2] : (tensor<1x4x4x8xf32>) -> tensor<1x8x4x4xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 10 04:07:09 UTC 2024 - 5.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/tests/passes/nchw_convolution_to_nhwc.mlir
// CHECK: %[[TRANSPOSE_2:.+]] = stablehlo.transpose %[[CONV]], dims = [0, 3, 1, 2] : (tensor<1x4x4x8xf32>) -> tensor<1x8x4x4xf32> // ----- // Tests that the conversion doesn't happen when the input dimension numbers // are not [b, f, 0, 1]. // CHECK-LABEL: conv_input_dim_numbers_mismatch
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 25 23:00:47 UTC 2024 - 5.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_layout_assignment_to_nchw.mlir
padding = "EXPLICIT", strides = [5, 6, 7, 8] } : (tensor<1x32x32x3xf32>, tensor<1x1x3x8xf32>) -> tensor<1x7x7x8xf32> func.return %0 : tensor<1x7x7x8xf32> } // CHECK-LABEL: func @transposeConv2DWithDefaultAttr func.func @transposeConv2DWithDefaultAttr(%input: tensor<1x32x32x3xf32>, %filter: tensor<1x1x3x8xf32>) -> tensor<?x?x?x?xf32> {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_layout_assignment_to_nhwc.mlir
// CHECK-SAME: explicit_paddings = [1, 2, 5, 6, 7, 8, 3, 4] // CHECK-SAME: padding = "EXPLICIT" // CHECK-SAME: strides = [5, 7, 8, 6] // CHECK-SAME: (tensor<1x32x32x3xf32>, tensor<1x1x3x8xf32>) -> tensor<1x7x6x8xf32> // CHECK: %[[RES_PERM:.*]] = "tf.Const"() <{value = dense<[0, 3, 1, 2]> : tensor<4xi64>}> // CHECK: %[[RES_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%[[CONV2D]], %[[RES_PERM]]) // CHECK: return %[[RES_TRANSPOSE]]
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 4.5K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/tf-ops.mlir
// CHECK-LABEL: func @testValidFakeQuantWithMinMaxArgs func.func @testValidFakeQuantWithMinMaxArgs(tensor<8x8x8x8xf32>) -> tensor<8x8x8x8xf32> { ^bb0(%arg0: tensor<8x8x8x8xf32>): %0 = "tf.FakeQuantWithMinMaxArgs"(%arg0) {min = -1.0 : f32, max = 1.0 : f32, num_bits = 3} : (tensor<8x8x8x8xf32>) -> tensor<8x8x8x8xf32> func.return %0 : tensor<8x8x8x8xf32> } // ----- // Test invalid tf.FakeQuantWithMinMaxArgs
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 23 14:40:35 UTC 2023 - 236.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_move_transposes_begin.mlir
%1 = "tf.AddV2"(%0, %0) : (tensor<1x4x4x8xf32>, tensor<1x4x4x8xf32>) -> tensor<1x4x4x8xf32> %2 = "tf.Const"() {value = dense<[0, 3, 1, 2]> : tensor<4xi32>} : () -> tensor<4xi32> %3 = "tf.Transpose"(%1, %2) : (tensor<1x4x4x8xf32>, tensor<4xi32>) -> tensor<1x8x4x4xf32> func.return %3 : tensor<1x8x4x4xf32> } // CHECK-LABEL: move_transpose_handle_broadcast
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 6.3K bytes - Viewed (0)