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[NNPA] Update configurations for test cases of backend test for dynamic dimensions #2831

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Merged
merged 10 commits into from
Jun 12, 2024
Merged

[NNPA] Update configurations for test cases of backend test for dynamic dimensions #2831

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0cbd8b0
Enable some of test cases for dynamic dimension for NNPA.
imaihal May 21, 2024
37381db
Merge branch 'main' into backendtest_dynamic
imaihal May 23, 2024
0f392ec
Move comments of each line to `==LIM==`
imaihal May 23, 2024
73350bb
Update condiftion for rewriting ConvTranspose op
imaihal May 27, 2024
efd5ee3
Update condition for rwriting Convtranspose op
imaihal May 30, 2024
b514446
Merge branch 'main' into backendtest_dynamic
imaihal Jun 11, 2024
60e51ea
Remove NO_DYNAMIC_SHAPE_TEST in ConvTranspose op.
imaihal Jun 11, 2024
d999426
Use dimAnalysis in legality check.
imaihal Jun 12, 2024
ec65ac6
Clean up config for dynamic backend tests.
imaihal Jun 12, 2024
b703fcf
Merge branch 'main' into backendtest_dynamic
imaihal Jun 12, 2024
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3 changes: 2 additions & 1 deletion src/Accelerators/NNPA/Conversion/ONNXToZHigh/ONNXLegalityCheck.cpp
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Expand Up @@ -103,7 +103,8 @@ bool checkLegalityPoolOpsCommon(POOLOP op, Value Y) {
// Check "MaxPool2D/AvgPool2D Parameter Restrictions". These restrictions are
// described in "zDNN API Reference". Input tensor N(batchNum) and C(Channel)
// dimensions must always match the output tensor's respective dimensions.
if (shapeInput[0] != shapeOutput[0] || shapeInput[1] != shapeOutput[1])
if ((inputType.hasStaticShape() && outputType.hasStaticShape()) &&
(shapeInput[0] != shapeOutput[0] || shapeInput[1] != shapeOutput[1]))
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Can we use DimAnalysis to check dynamic dims here?

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Done. Thanks!

return false;

// Check if kernelShape is literal. Only static value is supported.
Expand Down
60 changes: 30 additions & 30 deletions test/accelerators/NNPA/backend/CMakeLists.txt
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Expand Up @@ -118,32 +118,32 @@ set(NNPA_TEST_LIST
# ==LIM== - `auto_pad` must be `NOTSET`, `VALID`, and `SAME_UPPER`. If `NOTSET` is used, `pads` must be set so that the padding valid type or same upper.<br>- `ceil_mode` must be default value(0) <br>- Input and output tensors must be 4D tensors (N x C x H x W).<br>- `kernel_shape` must be static.<br>- `count_include_pad` must be default value(0).<br>- `ceil_mode` must be default value(0).
# test_averagepool_1d_default_cpu
# test_averagepool_2d_ceil_cpu
test_averagepool_2d_default_cpu,zdnn_avgpool2d,NO_DYNAMIC_SHAPE_TEST
test_averagepool_2d_default_cpu,zdnn_avgpool2d
# test_averagepool_2d_pads_count_include_pad_cpu
# test_averagepool_2d_pads_cpu
# test_averagepool_2d_precomputed_pads_count_include_pad_cpu
test_averagepool_2d_precomputed_pads_cpu,zdnn_avgpool2d,NO_DYNAMIC_SHAPE_TEST
test_averagepool_2d_precomputed_same_upper_cpu,zdnn_avgpool2d,NO_DYNAMIC_SHAPE_TEST
test_averagepool_2d_precomputed_strides_cpu,zdnn_avgpool2d,NO_DYNAMIC_SHAPE_TEST
test_averagepool_2d_precomputed_pads_cpu,zdnn_avgpool2d,NO_DYNAMIC_SHAPE_TEST # Padding type is not `SAME_PADDING` or `VALID_PADDING`
test_averagepool_2d_precomputed_same_upper_cpu,zdnn_avgpool2d
test_averagepool_2d_precomputed_strides_cpu,zdnn_avgpool2d
# test_averagepool_2d_same_lower_cpu
test_averagepool_2d_same_upper_cpu,zdnn_avgpool2d,NO_DYNAMIC_SHAPE_TEST
test_averagepool_2d_strides_cpu,zdnn_avgpool2d,NO_DYNAMIC_SHAPE_TEST
test_averagepool_2d_same_upper_cpu,zdnn_avgpool2d
test_averagepool_2d_strides_cpu,zdnn_avgpool2d
# test_averagepool_3d_default_cpu

# ==OP== BatchNormalization
# ==MIN== 6
# ==LIM== Input and output tensor must be 4D(N x C x H x W).
test_batchnorm_epsilon_cpu,zdnn_mul_ext,NO_DYNAMIC_SHAPE_TEST
test_batchnorm_example_cpu,zdnn_mul_ext,NO_DYNAMIC_SHAPE_TEST
test_batchnorm_epsilon_cpu,zdnn_mul_ext,"0:0=a,1=b,2=c,3=d|1:0=b|2:0=b|3:0=b|4:0=b"
test_batchnorm_example_cpu,zdnn_mul_ext,"0:0=a,1=b,2=c,3=d|1:0=b|2:0=b|3:0=b|4:0=b"

# ==OP== Conv
# ==MIN== 1
# ==LIM== - `auto_pad` must be `NOTSET`, `VALID`, and `SAME_UPPER`. If `NOTSET` is used, `pads` must be set so that the padding valid type or same upper.<br>- Dimension in Height and weight must be static.<br>- `group` must be default value(1).<br>- `dilations` must be default value(1).<br>- Input and output tensors must have 4D (N x C x H x W).<br>- `kernel_shape` must be static.
test_basic_conv_with_padding_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST
test_basic_conv_without_padding_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST
test_basic_conv_with_padding_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # Height and/or width must be static dimensions.
test_basic_conv_without_padding_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # Height and/or width must be static dimensions.
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Comments here look the same as ==LIM==, are they necessary?

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Removed. Thanks.

# test_conv_with_autopad_same_cpu
test_conv_with_strides_no_padding_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST
test_conv_with_strides_padding_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST
test_conv_with_strides_no_padding_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # Height and/or width must be static dimensions.
test_conv_with_strides_padding_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # Height and/or width must be static dimensions.
# test_conv_with_strides_and_asymmetric_padding_cpu

# ==OP== ConvTranspose
Expand All @@ -152,13 +152,13 @@ set(NNPA_TEST_LIST
# Disable backend tests for ConvTranspose, because they do not work on CPU.
# test_convtranspose_1d_cpu,zdnn_conv1d
# test_convtranspose_3d_cpu
test_convtranspose_autopad_same_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # not work on CPU
test_convtranspose_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # not work on CPU
test_convtranspose_autopad_same_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # Spatial dims must be static even on CPU.
test_convtranspose_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # Spatial dims must be static even on CPU.
# test_convtranspose_dilations_cpu,zdnn_conv2d
test_convtranspose_kernel_shape_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # not work on CPU
test_convtranspose_output_shape_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # not work on CPU
test_convtranspose_pad_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # not work on CPU
test_convtranspose_pads_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # not work on CPU
test_convtranspose_kernel_shape_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # Spatial dims must be static even on CPU.
test_convtranspose_output_shape_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # Spatial dims must be static even on CPU.
test_convtranspose_pad_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # Spatial dims must be static even on CPU.
test_convtranspose_pads_cpu,zdnn_conv2d,NO_DYNAMIC_SHAPE_TEST # Spatial dims must be static even on CPU.

# ==OP== Div
# ==MIN== 6
Expand Down Expand Up @@ -191,8 +191,8 @@ set(NNPA_TEST_LIST
# ==OP== GlobalAveragePool
# ==MIN== 1
# ==LIM== - Input shape must be 4D tensor(NCHW).<br>- Dimensions in `H` and `W` must be static.
test_globalaveragepool_cpu,zdnn_meanreduce2d,NO_DYNAMIC_SHAPE_TEST
test_globalaveragepool_precomputed_cpu,zdnn_meanreduce2d,NO_DYNAMIC_SHAPE_TEST
test_globalaveragepool_cpu,zdnn_meanreduce2d,NO_DYNAMIC_SHAPE_TEST # Height and Width dimension must be static dimension.
test_globalaveragepool_precomputed_cpu,zdnn_meanreduce2d,NO_DYNAMIC_SHAPE_TEST # Height and Width dimension must be static dimension.
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Comments here look the same as ==LIM==, are they necessary?

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Removed. Thanks.

# GlobalMaxPool
# test_globalmaxpool_cpu
# test_globalmaxpool_precomputed_cpu
Expand Down Expand Up @@ -222,7 +222,7 @@ set(NNPA_TEST_LIST
# test_logsoftmax_axis_0_cpu
# test_logsoftmax_axis_1_cpu
# test_logsoftmax_axis_2_cpu,zdnn_log_ext
test_logsoftmax_example_1_cpu,zdnn_softmax_ext,NO_DYNAMIC_SHAPE_TEST
test_logsoftmax_example_1_cpu,zdnn_softmax_ext
# test_logsoftmax_default_axis_cpu
# test_logsoftmax_negative_axis_cpu,zdnn_log_ext
# test_logsoftmax_large_number_cpu # accuracy error in test_logsoftmax_large_number_cpu
Expand All @@ -248,7 +248,7 @@ set(NNPA_TEST_LIST
#test_max_one_input_cpu
test_max_two_inputs_cpu,zdnn_max_ext,"0:0=a|1:0=a"
# test_max_float16_cpu
test_max_float32_cpu,zdnn_max_ext,NO_DYNAMIC_SHAPE_TEST
test_max_float32_cpu,zdnn_max_ext,"0:0=a|1:0=a"
# test_max_float64_cpu
# test_max_int8_cpu
# test_max_int16_cpu
Expand All @@ -264,15 +264,15 @@ set(NNPA_TEST_LIST
# ==LIM== - `auto_pad` must be `NOTSET`, `VALID`, and `SAME_UPPER`. If `NOTSET` is used, `pads` must be set so that the padding valid type or same upper.<br>- `ceil_mode` must be default value(0) <br>- Input and output tensors must be 4D tensors(N x C x H x W).<br>- `kernel_shape` must be static.<br>- `ceil_mode` must be default value(0).<br>- `dilations` must be default value(1).
# test_maxpool_1d_default_cpu
# test_maxpool_2d_ceil_cpu
test_maxpool_2d_default_cpu,zdnn_avgpool2d,NO_DYNAMIC_SHAPE_TEST
test_maxpool_2d_default_cpu,zdnn_maxpool2d
# test_maxpool_2d_dilations_cpu
# test_maxpool_2d_pads_cpu
# test_maxpool_2d_precomputed_pads_cpu
test_maxpool_2d_precomputed_same_upper_cpu,zdnn_avgpool2d,NO_DYNAMIC_SHAPE_TEST
test_maxpool_2d_precomputed_strides_cpu,zdnn_avgpool2d,NO_DYNAMIC_SHAPE_TEST
test_maxpool_2d_precomputed_pads_cpu,zdnn_maxpool2d,NO_DYNAMIC_SHAPE_TEST
test_maxpool_2d_precomputed_same_upper_cpu,zdnn_maxpool2d
test_maxpool_2d_precomputed_strides_cpu,zdnn_maxpool2d
# test_maxpool_2d_same_lower_cpu
test_maxpool_2d_same_upper_cpu,zdnn_avgpool2d,NO_DYNAMIC_SHAPE_TEST
test_maxpool_2d_strides_cpu,zdnn_avgpool2d,NO_DYNAMIC_SHAPE_TEST
test_maxpool_2d_same_upper_cpu,zdnn_maxpool2d
test_maxpool_2d_strides_cpu,zdnn_maxpool2d
# test_maxpool_3d_default_cpu

# ==OP== Min
Expand All @@ -282,7 +282,7 @@ set(NNPA_TEST_LIST
# test_min_one_input_cpu
test_min_two_inputs_cpu,zdnn_min_ext,"0:0=a|1:0=a"
# test_min_float16_cpu
test_min_float32_cpu,zdnn_min_ext,NO_DYNAMIC_SHAPE_TEST
test_min_float32_cpu,zdnn_min_ext,"0:0=a|1:0=a"
# test_min_float64_cpu
# test_min_int8_cpu
# test_min_int16_cpu
Expand Down Expand Up @@ -329,7 +329,7 @@ set(NNPA_TEST_LIST
# test_softmax_axis_1_cpu
# test_softmax_axis_2_cpu
# test_softmax_default_axis_cpu
test_softmax_example_cpu,zdnn_softmax_ext,NO_DYNAMIC_SHAPE_TEST
test_softmax_example_cpu,zdnn_softmax_ext
# test_softmax_large_number_cpu # accuracy error

# ==OP== Sub
Expand Down
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