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Commit b65e32e2 authored by nishant.b.patel's avatar nishant.b.patel
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Add back the type_prop tests

parent bd4f627b
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test/type_prop.cpp
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...@@ -15263,3 +15263,609 @@ TEST(type_prop, group_conv_transpose_invalid_params) ...@@ -15263,3 +15263,609 @@ TEST(type_prop, group_conv_transpose_invalid_params)
std::string("Output padding should be of number of input data features size.")); std::string("Output padding should be of number of input data features size."));
} }
} }
TEST(type_prop, quantized_conv_8_bit_output)
{
auto strides = Strides{1, 1};
auto dilation = Strides{1, 1};
auto padding_below = CoordinateDiff{1, 1};
auto padding_above = CoordinateDiff{1, 1};
element::Type f32 = element::f32;
element::Type i8 = element::i8;
element::Type u8 = element::u8;
element::Type input_type = u8;
element::Type filter_type = i8;
element::Type output_type = i8;
element::Type scale_type = f32;
element::Type input_zero_point_type = u8;
element::Type filter_zero_point_type = i8;
element::Type output_zero_point_type = i8;
Shape output_shape{64, 64, 220, 220};
AxisSet axes{};
auto input = make_shared<op::Parameter>(input_type, Shape{64, 3, 224, 224});
auto filter = make_shared<op::Parameter>(filter_type, Shape{64, 3, 7, 7});
auto scale = make_shared<op::Parameter>(scale_type, Shape{});
auto i8_zero_point = make_shared<op::Parameter>(element::i8, Shape{});
auto u8_zero_point = make_shared<op::Parameter>(element::u8, Shape{});
auto quant_conv = make_shared<op::QuantizedConvolution>(input,
filter,
strides,
dilation,
padding_below,
padding_above,
dilation,
scale,
u8_zero_point,
scale,
i8_zero_point,
scale,
i8_zero_point,
output_type,
axes,
axes,
axes);
ASSERT_EQ(quant_conv->get_element_type(), output_type);
ASSERT_EQ(quant_conv->get_shape(), output_shape);
}
TEST(type_prop, quantized_conv_32_bit_output)
{
auto strides = Strides{1, 1};
auto dilation = Strides{1, 1};
auto padding_below = CoordinateDiff{1, 1};
auto padding_above = CoordinateDiff{1, 1};
element::Type f32 = element::f32;
element::Type i8 = element::i8;
element::Type u8 = element::u8;
element::Type i32 = element::i32;
element::Type input_type = u8;
element::Type filter_type = i8;
element::Type output_type = i32;
element::Type scale_type = f32;
element::Type input_zero_point_type = u8;
element::Type filter_zero_point_type = i8;
element::Type output_zero_point_type = i8;
Shape output_shape{64, 64, 220, 220};
AxisSet axes{};
auto input = make_shared<op::Parameter>(input_type, Shape{64, 3, 224, 224});
auto filter = make_shared<op::Parameter>(filter_type, Shape{64, 3, 7, 7});
auto scale = make_shared<op::Parameter>(scale_type, Shape{});
auto i8_zero_point = make_shared<op::Parameter>(element::i8, Shape{});
auto u8_zero_point = make_shared<op::Parameter>(element::u8, Shape{});
auto quant_conv = make_shared<op::QuantizedConvolution>(input,
filter,
strides,
dilation,
padding_below,
padding_above,
dilation,
scale,
u8_zero_point,
scale,
i8_zero_point,
scale,
i8_zero_point,
output_type,
axes,
axes,
axes);
ASSERT_EQ(quant_conv->get_element_type(), output_type);
ASSERT_EQ(quant_conv->get_shape(), output_shape);
}
TEST(type_prop, quantized_conv_non_quantized_input_fails)
{
auto strides = Strides{1, 1};
auto dilation = Strides{1, 1};
auto padding_below = CoordinateDiff{1, 1};
auto padding_above = CoordinateDiff{1, 1};
element::Type f32 = element::f32;
element::Type i8 = element::i8;
element::Type u8 = element::u8;
element::Type input_type = f32;
element::Type filter_type = i8;
element::Type output_type = i8;
element::Type scale_type = f32;
element::Type input_zero_point_type = u8;
element::Type filter_zero_point_type = i8;
element::Type output_zero_point_type = i8;
Shape output_shape{64, 64, 220, 220};
AxisSet axes{};
auto input = make_shared<op::Parameter>(input_type, Shape{64, 3, 224, 224});
auto filter = make_shared<op::Parameter>(filter_type, Shape{64, 3, 7, 7});
auto scale = make_shared<op::Parameter>(scale_type, Shape{});
auto i8_zero_point = make_shared<op::Parameter>(element::i8, Shape{});
auto u8_zero_point = make_shared<op::Parameter>(element::u8, Shape{});
try
{
auto quant_conv = make_shared<op::QuantizedConvolution>(input,
filter,
strides,
dilation,
padding_below,
padding_above,
dilation,
scale,
u8_zero_point,
scale,
i8_zero_point,
scale,
i8_zero_point,
output_type,
axes,
axes,
axes);
FAIL() << "Attempt to use non-quantized input not detected";
}
catch (const NodeValidationFailure& error)
{
EXPECT_HAS_SUBSTRING(error.what(),
"Input element type (element::Type{32, 1, 1, 0, \"float\"}) "
"must be a quantized type");
}
catch (...)
{
FAIL() << "Deduced type check failed for unexpected reason";
}
}
TEST(type_prop, quantized_conv_non_quantized_filter_fails)
{
auto strides = Strides{1, 1};
auto dilation = Strides{1, 1};
auto padding_below = CoordinateDiff{1, 1};
auto padding_above = CoordinateDiff{1, 1};
element::Type f32 = element::f32;
element::Type i8 = element::i8;
element::Type u8 = element::u8;
element::Type input_type = u8;
element::Type filter_type = f32;
element::Type output_type = i8;
element::Type scale_type = f32;
element::Type input_zero_point_type = u8;
element::Type filter_zero_point_type = i8;
element::Type output_zero_point_type = i8;
Shape output_shape{64, 64, 220, 220};
AxisSet axes{};
auto input = make_shared<op::Parameter>(input_type, Shape{64, 3, 224, 224});
auto filter = make_shared<op::Parameter>(filter_type, Shape{64, 3, 7, 7});
auto scale = make_shared<op::Parameter>(scale_type, Shape{});
auto i8_zero_point = make_shared<op::Parameter>(element::i8, Shape{});
auto u8_zero_point = make_shared<op::Parameter>(element::u8, Shape{});
try
{
auto quant_conv = make_shared<op::QuantizedConvolution>(input,
filter,
strides,
dilation,
padding_below,
padding_above,
dilation,
scale,
u8_zero_point,
scale,
i8_zero_point,
scale,
i8_zero_point,
output_type,
axes,
axes,
axes);
FAIL() << "Attempt to use non-quantized filter not detected";
}
catch (const NodeValidationFailure& error)
{
EXPECT_HAS_SUBSTRING(error.what(),
"Filter element type (element::Type{32, 1, 1, 0, \"float\"}) "
"must be a quantized type");
}
catch (...)
{
FAIL() << "Deduced type check failed for unexpected reason";
}
}
TEST(type_prop, quantized_conv_dyn_output_fails)
{
auto strides = Strides{1, 1};
auto dilation = Strides{1, 1};
auto padding_below = CoordinateDiff{1, 1};
auto padding_above = CoordinateDiff{1, 1};
element::Type f32 = element::f32;
element::Type i8 = element::i8;
element::Type u8 = element::u8;
element::Type input_type = u8;
element::Type filter_type = f32;
element::Type output_type = element::dynamic;
element::Type scale_type = f32;
element::Type input_zero_point_type = u8;
element::Type filter_zero_point_type = i8;
element::Type output_zero_point_type = i8;
Shape output_shape{64, 64, 220, 220};
AxisSet axes{};
auto input = make_shared<op::Parameter>(input_type, Shape{64, 3, 224, 224});
auto filter = make_shared<op::Parameter>(filter_type, Shape{64, 3, 7, 7});
auto scale = make_shared<op::Parameter>(scale_type, Shape{});
auto i8_zero_point = make_shared<op::Parameter>(element::i8, Shape{});
auto u8_zero_point = make_shared<op::Parameter>(element::u8, Shape{});
try
{
auto quant_conv = make_shared<op::QuantizedConvolution>(input,
filter,
strides,
dilation,
padding_below,
padding_above,
dilation,
scale,
u8_zero_point,
scale,
i8_zero_point,
scale,
i8_zero_point,
output_type,
axes,
axes,
axes);
FAIL() << "Attempt to use dynamic output type not detected";
}
catch (const NodeValidationFailure& error)
{
EXPECT_HAS_SUBSTRING(error.what(), "Output element type must not be dynamic");
}
catch (...)
{
FAIL() << "Deduced type check failed for unexpected reason";
}
}
TEST(type_prop, quantized_conv_non_floating_point_scale_fails)
{
auto strides = Strides{1, 1};
auto dilation = Strides{1, 1};
auto padding_below = CoordinateDiff{1, 1};
auto padding_above = CoordinateDiff{1, 1};
element::Type f32 = element::f32;
element::Type i8 = element::i8;
element::Type u8 = element::u8;
element::Type input_type = u8;
element::Type filter_type = i8;
element::Type output_type = i8;
element::Type scale_type = i8;
element::Type input_zero_point_type = u8;
element::Type filter_zero_point_type = i8;
element::Type output_zero_point_type = i8;
Shape output_shape{64, 64, 220, 220};
AxisSet axes{};
auto input = make_shared<op::Parameter>(input_type, Shape{64, 3, 224, 224});
auto filter = make_shared<op::Parameter>(filter_type, Shape{64, 3, 7, 7});
auto scale = make_shared<op::Parameter>(scale_type, Shape{});
auto i8_zero_point = make_shared<op::Parameter>(element::i8, Shape{});
auto u8_zero_point = make_shared<op::Parameter>(element::u8, Shape{});
try
{
auto quant_conv = make_shared<op::QuantizedConvolution>(input,
filter,
strides,
dilation,
padding_below,
padding_above,
dilation,
scale,
u8_zero_point,
scale,
i8_zero_point,
scale,
i8_zero_point,
output_type,
axes,
axes,
axes);
FAIL() << "Attempt to use non floating point scale not detected";
}
catch (const NodeValidationFailure& error)
{
EXPECT_HAS_SUBSTRING(error.what(), "Scale must be a floating point number");
}
catch (...)
{
FAIL() << "Deduced type check failed for unexpected reason";
}
}
TEST(type_prop, quantized_conv_input_zero_point_type_mismatch_fails)
{
auto strides = Strides{1, 1};
auto dilation = Strides{1, 1};
auto padding_below = CoordinateDiff{1, 1};
auto padding_above = CoordinateDiff{1, 1};
element::Type f32 = element::f32;
element::Type i8 = element::i8;
element::Type u8 = element::u8;
element::Type input_type = u8;
element::Type filter_type = i8;
element::Type output_type = i8;
element::Type scale_type = f32;
element::Type input_zero_point_type = i8;
element::Type filter_zero_point_type = i8;
element::Type output_zero_point_type = i8;
Shape output_shape{64, 64, 220, 220};
AxisSet axes{};
auto input = make_shared<op::Parameter>(input_type, Shape{64, 3, 224, 224});
auto filter = make_shared<op::Parameter>(filter_type, Shape{64, 3, 7, 7});
auto scale = make_shared<op::Parameter>(scale_type, Shape{});
auto input_zero_point = make_shared<op::Parameter>(input_zero_point_type, Shape{});
auto filter_zero_point = make_shared<op::Parameter>(filter_zero_point_type, Shape{});
auto output_zero_point = make_shared<op::Parameter>(output_zero_point_type, Shape{});
try
{
auto quant_conv = make_shared<op::QuantizedConvolution>(input,
filter,
strides,
dilation,
padding_below,
padding_above,
dilation,
scale,
input_zero_point,
scale,
filter_zero_point,
scale,
output_zero_point,
output_type,
axes,
axes,
axes);
FAIL() << "Attempt to use zero point type different from input type not detected";
}
catch (const NodeValidationFailure& error)
{
EXPECT_HAS_SUBSTRING(
error.what(),
"Input Zero point element type (element::Type{8, 0, 1, 1, \"int8_t\"}) must "
"match input element type (element::Type{8, 0, 0, 1, \"uint8_t\"})");
}
catch (...)
{
FAIL() << "Deduced type check failed for unexpected reason";
}
}
TEST(type_prop, quantized_conv_filter_zero_point_type_mismatch_fails)
{
auto strides = Strides{1, 1};
auto dilation = Strides{1, 1};
auto padding_below = CoordinateDiff{1, 1};
auto padding_above = CoordinateDiff{1, 1};
element::Type f32 = element::f32;
element::Type i8 = element::i8;
element::Type u8 = element::u8;
element::Type input_type = u8;
element::Type filter_type = i8;
element::Type output_type = i8;
element::Type scale_type = f32;
element::Type input_zero_point_type = u8;
element::Type filter_zero_point_type = u8;
element::Type output_zero_point_type = i8;
Shape output_shape{64, 64, 220, 220};
AxisSet axes{};
auto input = make_shared<op::Parameter>(input_type, Shape{64, 3, 224, 224});
auto filter = make_shared<op::Parameter>(filter_type, Shape{64, 3, 7, 7});
auto scale = make_shared<op::Parameter>(scale_type, Shape{});
auto input_zero_point = make_shared<op::Parameter>(input_zero_point_type, Shape{});
auto filter_zero_point = make_shared<op::Parameter>(filter_zero_point_type, Shape{});
auto output_zero_point = make_shared<op::Parameter>(output_zero_point_type, Shape{});
try
{
auto quant_conv = make_shared<op::QuantizedConvolution>(input,
filter,
strides,
dilation,
padding_below,
padding_above,
dilation,
scale,
input_zero_point,
scale,
filter_zero_point,
scale,
output_zero_point,
output_type,
axes,
axes,
axes);
FAIL() << "Attempt to use zero point type different from filter type not detected";
}
catch (const NodeValidationFailure& error)
{
EXPECT_HAS_SUBSTRING(
error.what(),
"Filter Zero point element type (element::Type{8, 0, 0, 1, \"uint8_t\"}) must "
"match filter element type (element::Type{8, 0, 1, 1, \"int8_t\"})");
}
catch (...)
{
FAIL() << "Deduced type check failed for unexpected reason";
}
}
TEST(type_prop, quantized_conv_non_scalar_input_zero_point_fails)
{
auto strides = Strides{1, 1};
auto dilation = Strides{1, 1};
auto padding_below = CoordinateDiff{1, 1};
auto padding_above = CoordinateDiff{1, 1};
element::Type f32 = element::f32;
element::Type i8 = element::i8;
element::Type u8 = element::u8;
element::Type input_type = u8;
element::Type filter_type = i8;
element::Type output_type = i8;
element::Type scale_type = f32;
element::Type input_zero_point_type = u8;
element::Type filter_zero_point_type = i8;
element::Type output_zero_point_type = i8;
Shape output_shape{64, 64, 220, 220};
AxisSet axes{};
auto input = make_shared<op::Parameter>(input_type, Shape{64, 3, 224, 224});
auto filter = make_shared<op::Parameter>(filter_type, Shape{64, 3, 7, 7});
auto scale = make_shared<op::Parameter>(scale_type, Shape{});
auto input_zero_point = make_shared<op::Parameter>(input_zero_point_type, Shape{1, 2});
auto filter_zero_point = make_shared<op::Parameter>(filter_zero_point_type, Shape{});
auto output_zero_point = make_shared<op::Parameter>(output_zero_point_type, Shape{});
try
{
auto quant_conv = make_shared<op::QuantizedConvolution>(input,
filter,
strides,
dilation,
padding_below,
padding_above,
dilation,
scale,
input_zero_point,
scale,
filter_zero_point,
scale,
output_zero_point,
output_type,
axes,
axes,
axes);
FAIL() << "Attempt to use non scalar input zero point not detected";
}
catch (const NodeValidationFailure& error)
{
EXPECT_HAS_SUBSTRING(error.what(),
"Input scale and input zero point shape must be same and 1");
}
catch (...)
{
FAIL() << "Deduced type check failed for unexpected reason";
}
}
TEST(type_prop, quantized_conv_non_scalar_filter_zero_point_fails)
{
auto strides = Strides{1, 1};
auto dilation = Strides{1, 1};
auto padding_below = CoordinateDiff{1, 1};
auto padding_above = CoordinateDiff{1, 1};
element::Type f32 = element::f32;
element::Type i8 = element::i8;
element::Type u8 = element::u8;
element::Type input_type = u8;
element::Type filter_type = i8;
element::Type output_type = i8;
element::Type scale_type = f32;
element::Type input_zero_point_type = u8;
element::Type filter_zero_point_type = i8;
element::Type output_zero_point_type = i8;
Shape output_shape{64, 64, 220, 220};
AxisSet axes{};
auto input = make_shared<op::Parameter>(input_type, Shape{64, 3, 224, 224});
auto filter = make_shared<op::Parameter>(filter_type, Shape{64, 3, 7, 7});
auto scale = make_shared<op::Parameter>(scale_type, Shape{});
auto input_zero_point = make_shared<op::Parameter>(input_zero_point_type, Shape{});
auto filter_zero_point = make_shared<op::Parameter>(filter_zero_point_type, Shape{1, 2});
auto output_zero_point = make_shared<op::Parameter>(output_zero_point_type, Shape{});
try
{
auto quant_conv = make_shared<op::QuantizedConvolution>(input,
filter,
strides,
dilation,
padding_below,
padding_above,
dilation,
scale,
input_zero_point,
scale,
filter_zero_point,
scale,
output_zero_point,
output_type,
axes,
axes,
axes);
FAIL() << "Attempt to use non scalar filter zero point not detected";
}
catch (const NodeValidationFailure& error)
{
EXPECT_HAS_SUBSTRING(error.what(),
"Filter scale and filter zero point shape must be same and 1");
}
catch (...)
{
FAIL() << "Deduced type check failed for unexpected reason";
}
}
TEST(type_prop, quantized_conv_non_scalar_output_zero_point_fails)
{
auto strides = Strides{1, 1};
auto dilation = Strides{1, 1};
auto padding_below = CoordinateDiff{1, 1};
auto padding_above = CoordinateDiff{1, 1};
element::Type f32 = element::f32;
element::Type i8 = element::i8;
element::Type u8 = element::u8;
element::Type input_type = u8;
element::Type filter_type = i8;
element::Type output_type = i8;
element::Type scale_type = f32;
element::Type input_zero_point_type = u8;
element::Type filter_zero_point_type = i8;
element::Type output_zero_point_type = i8;
Shape output_shape{64, 64, 220, 220};
AxisSet axes{};
auto input = make_shared<op::Parameter>(input_type, Shape{64, 3, 224, 224});
auto filter = make_shared<op::Parameter>(filter_type, Shape{64, 3, 7, 7});
auto scale = make_shared<op::Parameter>(scale_type, Shape{});
auto input_zero_point = make_shared<op::Parameter>(input_zero_point_type, Shape{});
auto filter_zero_point = make_shared<op::Parameter>(filter_zero_point_type, Shape{});
auto output_zero_point = make_shared<op::Parameter>(output_zero_point_type, Shape{1, 2});
try
{
auto quant_conv = make_shared<op::QuantizedConvolution>(input,
filter,
strides,
dilation,
padding_below,
padding_above,
dilation,
scale,
input_zero_point,
scale,
filter_zero_point,
scale,
output_zero_point,
output_type,
axes,
axes,
axes);
FAIL() << "Attempt to use non scalar output zero point not detected";
}
catch (const NodeValidationFailure& error)
{
EXPECT_HAS_SUBSTRING(error.what(),
"Output scale and output zero point shape must be same and 1");
}
catch (...)
{
FAIL() << "Deduced type check failed for unexpected reason";
}
}
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