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Merge pull request #279 from Xilinx/chaitany.convtranspose_as_option
Chaitany.convtranspose as option
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104
test/mlir/onnx/onnx_decompose_convtranspose_disable.mlir
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| Original file line number | Diff line number | Diff line change |
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| // RUN: onnx-mlir-opt --shape-inference --decompose-onnx --disable-convtranspose-decompose %s -split-input-file | FileCheck %s | ||
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| // ----- | ||
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| // Test unit strides. Only convert weight tensor | ||
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| func.func @test_convtrans_unitstrides(%arg0: tensor<1x1x3x3xf32>, %arg1: tensor<1x2x3x3xf32>) -> tensor<1x2x5x5xf32> { | ||
| %0 = "onnx.NoValue"() {value} : () -> none | ||
| %1 = "onnx.ConvTranspose"(%arg0, %arg1, %0) {auto_pad = "NOTSET", group = 1 : si64} : (tensor<1x1x3x3xf32>, tensor<1x2x3x3xf32>, none) -> tensor<1x2x5x5xf32> | ||
| onnx.Return %1 : tensor<1x2x5x5xf32> | ||
| // CHECK-LABEL: func.func @test_convtrans_unitstrides( | ||
| // CHECK-SAME: %[[VAL_0:.*]]: tensor<1x1x3x3xf32>, | ||
| // CHECK-SAME: %[[VAL_1:.*]]: tensor<1x2x3x3xf32>) -> tensor<1x2x5x5xf32> { | ||
| // CHECK: %[[VAL_2:.*]] = "onnx.NoValue"() {value} : () -> none | ||
| // CHECK: %[[VAL_3:.*]] = "onnx.ConvTranspose"(%[[VAL_0]], %[[VAL_1]], %[[VAL_2]]) {auto_pad = "NOTSET", group = 1 : si64} : (tensor<1x1x3x3xf32>, tensor<1x2x3x3xf32>, none) -> tensor<1x2x5x5xf32> | ||
| // CHECK: onnx.Return %[[VAL_3]] : tensor<1x2x5x5xf32> | ||
| // CHECK: } | ||
| } | ||
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| // ----- | ||
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| // Test 1d input | ||
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| func.func @test_convtrans1d_unitstrides(%arg0: tensor<1x1x3xf32>, %arg1: tensor<1x2x3xf32>) -> tensor<1x2x5xf32> { | ||
| %0 = "onnx.NoValue"() {value} : () -> none | ||
| %1 = "onnx.ConvTranspose"(%arg0, %arg1, %0) {auto_pad = "NOTSET", group = 1 : si64} : (tensor<1x1x3xf32>, tensor<1x2x3xf32>, none) -> tensor<1x2x5xf32> | ||
| onnx.Return %1 : tensor<1x2x5xf32> | ||
| // CHECK-LABEL: func.func @test_convtrans1d_unitstrides( | ||
| // CHECK-SAME: %[[VAL_0:.*]]: tensor<1x1x3xf32>, | ||
| // CHECK-SAME: %[[VAL_1:.*]]: tensor<1x2x3xf32>) -> tensor<1x2x5xf32> { | ||
| // CHECK: %[[VAL_2:.*]] = "onnx.NoValue"() {value} : () -> none | ||
| // CHECK: %[[VAL_3:.*]] = "onnx.ConvTranspose"(%[[VAL_0]], %[[VAL_1]], %[[VAL_2]]) {auto_pad = "NOTSET", group = 1 : si64} : (tensor<1x1x3xf32>, tensor<1x2x3xf32>, none) -> tensor<1x2x5xf32> | ||
| // CHECK: onnx.Return %[[VAL_3]] : tensor<1x2x5xf32> | ||
| // CHECK: } | ||
| } | ||
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| // ----- | ||
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| // Test 3d input | ||
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| func.func @test_convtrans3d_unitstrides(%arg0: tensor<1x1x3x4x5xf32>, %arg1: tensor<1x2x3x3x3xf32>) -> tensor<1x2x5x6x7xf32> { | ||
| %0 = "onnx.NoValue"() {value} : () -> none | ||
| %1 = "onnx.ConvTranspose"(%arg0, %arg1, %0) {auto_pad = "NOTSET", group = 1 : si64} : (tensor<1x1x3x4x5xf32>, tensor<1x2x3x3x3xf32>, none) -> tensor<1x2x5x6x7xf32> | ||
| onnx.Return %1 : tensor<1x2x5x6x7xf32> | ||
| // CHECK-LABEL: func.func @test_convtrans3d_unitstrides( | ||
| // CHECK-SAME: %[[VAL_0:.*]]: tensor<1x1x3x4x5xf32>, | ||
| // CHECK-SAME: %[[VAL_1:.*]]: tensor<1x2x3x3x3xf32>) -> tensor<1x2x5x6x7xf32> { | ||
| // CHECK: %[[VAL_2:.*]] = "onnx.NoValue"() {value} : () -> none | ||
| // CHECK: %[[VAL_3:.*]] = "onnx.ConvTranspose"(%[[VAL_0]], %[[VAL_1]], %[[VAL_2]]) {auto_pad = "NOTSET", group = 1 : si64} : (tensor<1x1x3x4x5xf32>, tensor<1x2x3x3x3xf32>, none) -> tensor<1x2x5x6x7xf32> | ||
| // CHECK: onnx.Return %[[VAL_3]] : tensor<1x2x5x6x7xf32> | ||
| // CHECK: } | ||
| } | ||
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| // ----- | ||
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| // Test non unit strides. Added pads between elements in input data. | ||
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| func.func @test_convtrans_strides(%arg0: tensor<1x1x3x3xf32>, %arg1: tensor<1x2x3x3xf32>) -> tensor<1x2x7x3xf32> { | ||
| %0 = "onnx.NoValue"() {value} : () -> none | ||
| %1 = "onnx.ConvTranspose"(%arg0, %arg1, %0) {auto_pad = "NOTSET", group = 1 : si64, pads = [1, 2, 1, 2], strides = [3, 2]} : (tensor<1x1x3x3xf32>, tensor<1x2x3x3xf32>, none) -> tensor<1x2x7x3xf32> | ||
| onnx.Return %1 : tensor<1x2x7x3xf32> | ||
| // CHECK-LABEL: func.func @test_convtrans_strides( | ||
| // CHECK-SAME: %[[VAL_0:.*]]: tensor<1x1x3x3xf32>, | ||
| // CHECK-SAME: %[[VAL_1:.*]]: tensor<1x2x3x3xf32>) -> tensor<1x2x7x3xf32> { | ||
| // CHECK: %[[VAL_2:.*]] = "onnx.NoValue"() {value} : () -> none | ||
| // CHECK: %[[VAL_3:.*]] = "onnx.ConvTranspose"(%[[VAL_0]], %[[VAL_1]], %[[VAL_2]]) {auto_pad = "NOTSET", group = 1 : si64, pads = [1, 2, 1, 2], strides = [3, 2]} : (tensor<1x1x3x3xf32>, tensor<1x2x3x3xf32>, none) -> tensor<1x2x7x3xf32> | ||
| // CHECK: onnx.Return %[[VAL_3]] : tensor<1x2x7x3xf32> | ||
| // CHECK: } | ||
| } | ||
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| // ----- | ||
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| // Test output_padding. Additional pads are inserted after Conv op | ||
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| func.func @test_convtrans_outputpadding(%arg0: tensor<1x1x3x3xf32>, %arg1: tensor<1x2x3x3xf32>) -> tensor<1x2x10x8xf32> { | ||
| %0 = "onnx.NoValue"() {value} : () -> none | ||
| %1 = "onnx.ConvTranspose"(%arg0, %arg1, %0) {auto_pad = "NOTSET", group = 1 : si64, output_shape = [10, 8], strides = [3, 2]} : (tensor<1x1x3x3xf32>, tensor<1x2x3x3xf32>, none) -> tensor<1x2x10x8xf32> | ||
| onnx.Return %1 : tensor<1x2x10x8xf32> | ||
| // CHECK-LABEL: func.func @test_convtrans_outputpadding( | ||
| // CHECK-SAME: %[[VAL_0:.*]]: tensor<1x1x3x3xf32>, | ||
| // CHECK-SAME: %[[VAL_1:.*]]: tensor<1x2x3x3xf32>) -> tensor<1x2x10x8xf32> { | ||
| // CHECK: %[[VAL_2:.*]] = "onnx.NoValue"() {value} : () -> none | ||
| // CHECK: %[[VAL_3:.*]] = "onnx.ConvTranspose"(%[[VAL_0]], %[[VAL_1]], %[[VAL_2]]) {auto_pad = "NOTSET", group = 1 : si64, output_shape = [10, 8], strides = [3, 2]} : (tensor<1x1x3x3xf32>, tensor<1x2x3x3xf32>, none) -> tensor<1x2x10x8xf32> | ||
| // CHECK: onnx.Return %[[VAL_3]] : tensor<1x2x10x8xf32> | ||
| // CHECK: } | ||
| } | ||
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| // ----- | ||
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| // Test for unknown dimension in spatial dimensions | ||
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| func.func @test_convtranspose_unknown_spatial_dim(%arg0: tensor<?x?x3x3xf32>, %arg1: tensor<?x?x3x3xf32>) -> tensor<?x?x10x8xf32> { | ||
| %0 = "onnx.NoValue"() {value} : () -> none | ||
| %1 = "onnx.ConvTranspose"(%arg0, %arg1, %0) {auto_pad = "NOTSET", group = 1 : si64, kernel_shape = [3, 3], onnx_node_name = "test", output_padding = [1, 1], output_shape = [10, 8], strides = [3, 2]} : (tensor<?x?x3x3xf32>, tensor<?x?x3x3xf32>, none) -> tensor<?x?x10x8xf32> | ||
| onnx.Return %1 : tensor<?x?x10x8xf32> | ||
| // CHECK-LABEL: func.func @test_convtranspose_unknown_spatial_dim( | ||
| // CHECK-SAME: %[[VAL_0:.*]]: tensor<?x?x3x3xf32>, | ||
| // CHECK-SAME: %[[VAL_1:.*]]: tensor<?x?x3x3xf32>) -> tensor<?x?x10x8xf32> { | ||
| // CHECK: %[[VAL_2:.*]] = "onnx.NoValue"() {value} : () -> none | ||
| // CHECK: %[[VAL_3:.*]] = "onnx.ConvTranspose"(%[[VAL_0]], %[[VAL_1]], %[[VAL_2]]) {auto_pad = "NOTSET", group = 1 : si64, kernel_shape = [3, 3], onnx_node_name = "test", output_padding = [1, 1], output_shape = [10, 8], strides = [3, 2]} : (tensor<?x?x3x3xf32>, tensor<?x?x3x3xf32>, none) -> tensor<?x?x10x8xf32> | ||
| // CHECK: onnx.Return %[[VAL_3]] : tensor<?x?x10x8xf32> | ||
| // CHECK: } | ||
| } |