arm_compute v19.02
Change-Id: I853a3ecf38f206da13c1b03640c8adf73c20477c
diff --git a/tests/validation/CL/DeconvolutionLayer.cpp b/tests/validation/CL/DeconvolutionLayer.cpp
index 0b9ada7..31852c8 100644
--- a/tests/validation/CL/DeconvolutionLayer.cpp
+++ b/tests/validation/CL/DeconvolutionLayer.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2018 ARM Limited.
+ * Copyright (c) 2017-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -49,63 +49,24 @@
constexpr AbsoluteTolerance<float> tolerance_qasymm8(0.0); /**< Tolerance value for comparing reference's output against implementation's output for quantized data types */
constexpr float tolerance_num = 0.07f; /**< Tolerance number */
-const auto data4x4 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 5) * framework::dataset::make("StrideY", 1, 5) * framework::dataset::make("PadX", 0, 3)
- * framework::dataset::make("PadY", 0, 3) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 });
+const auto data4x4 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 3)
+ * framework::dataset::make("PadY", 0, 3) * framework::dataset::make("NumKernels", { 3 });
const auto data3x3 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 2)
- * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 });
+ * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("NumKernels", { 3 });
const auto data3x3_precommit = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 2) * framework::dataset::make("StrideY", 1, 2) * framework::dataset::make("PadX", 0, 2)
- * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 3 });
+ * framework::dataset::make("PadY", 0, 2) * framework::dataset::make("NumKernels", { 3 });
const auto data1x1 = datasets::SmallDeconvolutionShapes() * framework::dataset::make("StrideX", 1, 4) * framework::dataset::make("StrideY", 1, 4) * framework::dataset::make("PadX", 0, 1)
- * framework::dataset::make("PadY", 0, 1) * framework::dataset::make("ax", 0) * framework::dataset::make("ay", 0) * framework::dataset::make("NumKernels", { 1, 3 });
+ * framework::dataset::make("PadY", 0, 1) * framework::dataset::make("NumKernels", { 3 });
-const auto data_layouts_dataset = framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC });
+const auto data_layouts_dataset = framework::dataset::make("DataLayout", { DataLayout::NCHW });
} // namespace
TEST_SUITE(CL)
TEST_SUITE(DeconvolutionLayer)
-DATA_TEST_CASE(Configuration, framework::DatasetMode::ALL, (combine(datasets::SmallDeconvolutionShapes(), framework::dataset::make("DataType", DataType::F32))),
- input_shape, data_type)
-{
- // Create shapes
- const unsigned int kernel_size_x = 3;
- const unsigned int kernel_size_y = 3;
- const unsigned int num_kernels = 1;
- const TensorShape weights_shape(kernel_size_x, kernel_size_y, input_shape.z(), num_kernels);
- const TensorShape bias_shape(num_kernels);
- auto out_dim = deconvolution_output_dimensions(input_shape.x(), input_shape.y(), kernel_size_x, kernel_size_y, 1, 1, 1, 1);
- TensorShape output_shape = compute_deconvolution_output_shape(out_dim, TensorInfo(input_shape, 1, data_type), TensorInfo(weights_shape, 1, data_type));
-
- // Create tensors
- CLTensor src = create_tensor<CLTensor>(input_shape, data_type, 1);
- CLTensor weights = create_tensor<CLTensor>(weights_shape, data_type, 1);
- CLTensor bias = create_tensor<CLTensor>(bias_shape, data_type, 1);
- CLTensor dst = create_tensor<CLTensor>(output_shape, data_type, 1);
-
- ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(weights.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);
- ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
-
- // Create and configure function
- CLDeconvolutionLayer deconv;
- deconv.configure(&src, &weights, &bias, &dst, PadStrideInfo(1, 1, 1, 1, DimensionRoundingType::CEIL), 0, 0);
-
- // Validate valid region
- const ValidRegion src_valid_region = shape_to_valid_region(input_shape);
- const ValidRegion weights_valid_region = shape_to_valid_region(weights_shape);
- const ValidRegion bias_valid_region = shape_to_valid_region(bias_shape);
- const ValidRegion dst_valid_region = shape_to_valid_region(output_shape);
-
- validate(src.info()->valid_region(), src_valid_region);
- validate(weights.info()->valid_region(), weights_valid_region);
- validate(bias.info()->valid_region(), bias_valid_region);
- validate(dst.info()->valid_region(), dst_valid_region);
-}
-
// *INDENT-OFF*
// clang-format off
DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
@@ -113,12 +74,14 @@
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid weights shape
TensorInfo(TensorShape(27U, 13U, 2U), 1, DataType::F32), // Invalid bias shape
TensorInfo(TensorShape(13U, 11U, 4U, 3U), 1, DataType::F32), // Window shrink
+ TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32), // Inner border different from 0
TensorInfo(TensorShape(32U, 16U, 2U), 1, DataType::F32),
}),
framework::dataset::make("WeightsInfo", { TensorInfo(TensorShape(3U, 3U, 2U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(3U, 3U, 2U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(3U, 2U, 2U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(3U, 3U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(1U, 1U, 2U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(1U, 1U, 2U, 4U), 1, DataType::F32),
})),
framework::dataset::make("BiasInfo", { TensorInfo(TensorShape(1U), 1, DataType::F16),
@@ -127,32 +90,36 @@
TensorInfo(TensorShape(1U), 1, DataType::F32),
TensorInfo(TensorShape(4U), 1, DataType::F32),
TensorInfo(TensorShape(4U), 1, DataType::S32),
+ TensorInfo(TensorShape(4U), 1, DataType::S32),
})),
framework::dataset::make("OutputInfo",{ TensorInfo(TensorShape(25U, 11U, 2U), 1, DataType::F16),
TensorInfo(TensorShape(25U, 10U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(13U, 13U, 2U), 1, DataType::F32),
TensorInfo(TensorShape(11U, 9U, 1U, 3U), 1, DataType::F32),
TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32),
+ TensorInfo(TensorShape(32U, 16U, 4U), 1, DataType::F32),
})),
framework::dataset::make("PadStrideInfo", { PadStrideInfo(1, 1, 0, 0),
PadStrideInfo(1, 1, 0, 0),
PadStrideInfo(1, 1, 0, 0),
PadStrideInfo(1, 1, 1, 1),
PadStrideInfo(1, 1, 0, 0),
+ PadStrideInfo(1, 1, 0, 0),
})),
- framework::dataset::make("ax", { 1U,
- 1U,
- 1U,
+ framework::dataset::make("ax", { 0U,
+ 0U,
+ 0U,
0U,
0U,
})),
- framework::dataset::make("ay", { 1U,
- 1U,
- 1U,
+ framework::dataset::make("ay", { 0U,
0U,
0U,
+ 0U,
+ 1U,
+ 0U,
})),
- framework::dataset::make("Expected", { false, false, false, false, true })),
+ framework::dataset::make("Expected", { false, false, false, false, false, true })),
input_info, weights_info, bias_info, output_info, pad_info, ax, ay, expected)
{
bool is_valid = bool(CLDeconvolutionLayer::validate(&input_info.clone()->set_is_resizable(false), &weights_info.clone()->set_is_resizable(false), &bias_info.clone()->set_is_resizable(false), &output_info.clone()->set_is_resizable(false), pad_info, ax, ay));