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Results 1 - 10 of 16 for 1x32x32x8xf32 (0.36 sec)
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tensorflow/compiler/mlir/lite/tests/decompose-hybrid-quantization.mlir
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 13.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_layout_assignment_to_nchw.mlir
strides = [5, 6, 7, 8] } : (tensor<1x32x32x3xf32>, tensor<4xi32>, tensor<1x32x32x8xf32>) -> tensor<1x1x3x8xf32> func.return %0 : tensor<1x1x3x8xf32> } // CHECK-LABEL: func @transposeConv2DBackpropInput func.func @transposeConv2DBackpropInput( %input_sizes: tensor<4xi32>, %filter: tensor<1x1x3x8xf32>, %out_backprop: tensor<1x32x32x8xf32> ) -> tensor<1x32x32x3xf32> {
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/tf-ops.mlir
} // ----- func.func @testBiasAddNoDataFormatOk(tensor<1x32x32x16xf32>, tensor<16xf32>) -> tensor<1x32x32x16xf32> { ^bb0(%arg0: tensor<1x32x32x16xf32>, %arg1: tensor<16xf32>): %0 = "tf.BiasAdd"(%arg0, %arg1) {T = "tfdtype$DT_FLOAT"}: (tensor<1x32x32x16xf32>, tensor<16xf32>) -> tensor<1x32x32x16xf32> func.return %0 : tensor<1x32x32x16xf32> } // -----
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/lite/stablehlo/tests/odml-to-stablehlo-smuggle-resize.mlir
// CHECK-OPT: %{{.*}} = stablehlo.custom_call @tf.ResizeBilinear(%arg0, %cst) {align_corners = false, device = "", half_pixel_centers = true} : (tensor<1x32x32x128xf32>, tensor<2xi32>) -> tensor<1x64x64x128xf32> %1 = "tf.ResizeBilinear"(%arg0, %0) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Apr 14 18:33:43 UTC 2024 - 1.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/fused_kernel_matcher.mlir
// CHECK: %[[VAL_1:.*]] = "tf.Identity"(%[[VAL_0]]) : (tensor<*xf32>) -> tensor<*xf32> // CHECK: return %[[VAL_1]] %0 = "tf.Conv2D"(%arg2, %arg1) {data_format = "NHWC", dilations = [1, 1, 1, 1], explicit_paddings = [], padding = "SAME", strides = [1, 1, 1, 1], use_cudnn_on_gpu = true} : (tensor<8x32x32x3xf32>, tensor<1x1x3x128xf32>) -> tensor<*xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 13.2K bytes - Viewed (0) -
tensorflow/compiler/mlir/tf2xla/internal/passes/verify_clustering_pass_test.cc
module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 268 : i32}} { func.func @main() -> tensor<3x32x32x3xf32> { %0 = mhlo.constant dense<2.550000e+02> : tensor<3x32x32x3xf32> return %0 : tensor<3x32x32x3xf32> } })"; CreateModule(kMlirModuleStr); auto result = Run(); EXPECT_TRUE(result.failed()); } } // namespace
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 17:03:53 UTC 2023 - 2.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/composite-lowering.mlir
// CHECK: %1 = "tfl.transpose"(%arg0, %cst) : (tensor<4x8x32x32xf32>, tensor<4xi32>) -> tensor<4x32x32x8xf32> // CHECK: %cst_0 = arith.constant dense<64> : tensor<2xi32> // CHECK: %2 = "tfl.resize_nearest_neighbor"(%1, %cst_0) <{align_corners = false, half_pixel_centers = true}> : (tensor<4x32x32x8xf32>, tensor<2xi32>) -> tensor<4x64x64x8xf32> // CHECK: %cst_1 = arith.constant dense<[0, 3, 1, 2]> : tensor<4xi32>
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/lite/tests/get-arithmetic-count.mlir
func.return %0 : tensor<256x32x32x16xf32> } func.func @testConv2DDynamicShape(tensor<?x32x32x3xf32>, tensor<16x3x3x3xf32>, tensor<16xf32>) -> tensor<?x32x32x16xf32> { ^bb0(%arg0: tensor<?x32x32x3xf32>, %arg1: tensor<16x3x3x3xf32>, %arg2: tensor<16xf32>): // CHECK: _arithmetic_count = -1 : i64
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Dec 14 04:58:17 UTC 2022 - 7.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/constant-fold.mlir
// RUN: tf-opt %s -canonicalize | FileCheck %s // CHECK-LABEL: func @testShape func.func @testShape(tensor<f32>, tensor<1x32x32x16xf32>, tensor<*xf32>) -> (tensor<0xi32>, tensor<?xi32>, tensor<?xi32>) { ^bb0(%arg0: tensor<f32>, %arg1: tensor<1x32x32x16xf32>, %arg2: tensor<*xf32>): // CHECK-DAG: tf.Const{{.*}} dense<> : tensor<0xi32> %0 = "tf.Shape"(%arg0) {T = "tfdtype$DT_FLOAT", output = "tfdtype$DT_INT32"} : (tensor<f32>) -> tensor<0xi32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Jan 31 23:22:24 UTC 2024 - 36.7K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/tests/layout_optimization_layout_assignment_to_nhwc.mlir
// CHECK-SAME: dilations = [1, 3, 4, 2] // 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]])
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Oct 30 06:52:55 UTC 2023 - 4.5K bytes - Viewed (0)