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Results 1 - 3 of 3 for 4x8x32x32xf32 (0.14 sec)
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tensorflow/compiler/mlir/lite/stablehlo/tests/composite-lowering.mlir
return %1 : tensor<4x8x64x64xf32> } func.func private @XlaCallModule_tfl.resize_nearest_neighbor.impl_1(%arg0: tensor<4x8x32x32xf32>) -> tensor<4x8x64x64xf32> { %0 = call @XlaCallModule__resize_1(%arg0) : (tensor<4x8x32x32xf32>) -> tensor<4x8x64x64xf32> return %0 : tensor<4x8x64x64xf32> }
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/tensorflow/tests/layout_optimization_layout_assignment_to_nchw.mlir
// CHECK-SAME: dilations = [1, 4, 2, 3] // CHECK-SAME: explicit_paddings = [1, 2, 7, 8, 3, 4, 5, 6] // CHECK-SAME: padding = "EXPLICIT" // CHECK-SAME: strides = [5, 8, 6, 7] // CHECK-SAME: (tensor<1x3x32x32xf32>, tensor<4xi32>, tensor<1x8x32x32xf32>) // CHECK-SAME: -> tensor<1x1x3x8xf32> // CHECK: return %[[CONV2D_BACKPROP]] %0 = "tf.Conv2DBackpropFilter"(%input, %filter_sizes, %out_backprop) { data_format = "NHWC",
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
// dilations, etc...). This test only verifies that changing convolution data // layout will update all the attributes. // CHECK-LABEL: func @transposeConv2D func.func @transposeConv2D(%input: tensor<1x3x32x32xf32>, %filter: tensor<1x1x3x8xf32>) -> tensor<1x8x7x6xf32> { // CHECK: %[[ARG_PERM:.*]] = "tf.Const"() <{value = dense<[0, 2, 3, 1]> : tensor<4xi64>}> // CHECK: %[[ARG_TRANSPOSE:[0-9]*]] = "tf.Transpose"(%arg0, %[[ARG_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)