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[ONNX FE] Fix ONNX DequantizeLinear-13 import dynamic shape (#16966)

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Katarzyna Mitrus authored and GitHub committed 2023-04-18 13:03:55 +02:00
1 parent d5123056bb
commit 2a5c69abc6
5 files changed
+124 -40
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src/frontends/onnx/frontend/src/op/dequantize_linear.cpp
+3 -3
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@@ -72,7 +72,7 @@ void validate_scale(const Output<ngraph::Node> scale, const Output<ngraph::Node>
const auto& x_shape = x.get_partial_shape();
const auto& x_dim_at_axis = x_shape[axis];
NGRAPH_CHECK(scale_dim.same_scheme(x_dim_at_axis),
NGRAPH_CHECK(scale_dim.compatible(x_dim_at_axis),
"The number of dequantization scale elements '",
scale_dim,
"' must match the input shape dimension '",
@@ -92,7 +92,7 @@ void validate_zero_point(const Output<ngraph::Node> zero_point, const Output<ngr
const auto& x_shape = x.get_partial_shape();
const auto& x_dim_at_axis = x_shape[axis];
NGRAPH_CHECK(zero_point_dim.same_scheme(x_dim_at_axis),
NGRAPH_CHECK(zero_point_dim.compatible(x_dim_at_axis),
"The number of zero point elements '",
zero_point_dim,
"' must match the input shape dimension '",
@@ -122,7 +122,7 @@ std::shared_ptr<ngraph::Node> reshape_input(const Output<ngraph::Node>& input,
if (x_shape[axis].is_static()) {
target_dims.push_back(x_shape[axis].get_length());
} else {
target_dims.push_back(0);
target_dims.push_back(-1);
}
for (int64_t i = axis + 1; i < x_shape.rank().get_length(); ++i) {
src/frontends/onnx/tests/models/dequantize_linear_4_dynamic.prototxt
+91
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@@ -0,0 +1,91 @@
ir_version: 3
producer_name: "OpenVINO ONNX FE"
graph {
node {
input: "X"
input: "scale"
input: "zero_point"
output: "Y"
name: "node1"
op_type: "DequantizeLinear"
attribute {
name: "axis"
i: 1
type: INT
}
}
name: "test"
input {
name: "X"
type {
tensor_type {
elem_type: 3
shape {
dim {
dim_value: -1
}
dim {
dim_value: -1
}
dim {
dim_value: -1
}
dim {
dim_value: -1
}
}
}
}
}
input {
name: "scale"
type {
tensor_type {
elem_type: 1
shape {
dim {
dim_value: 3
}
}
}
}
}
input {
name: "zero_point"
type {
tensor_type {
elem_type: 3
shape {
dim {
dim_value: 3
}
}
}
}
}
output {
name: "Y"
type {
tensor_type {
elem_type: 1
shape {
dim {
dim_value: -1
}
dim {
dim_value: -1
}
dim {
dim_value: -1
}
dim {
dim_value: -1
}
}
}
}
}
}
opset_import {
version: 13
}
src/frontends/onnx/tests/onnx_import_quant.in.cpp
+30 -5
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@@ -269,6 +269,31 @@ NGRAPH_TEST(${BACKEND_NAME}, onnx_model_dequantize_linear_1d_zero_scale_int8) {
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, onnx_model_dequantize_linear_1d_zero_scale_int8_4d_dynamic) {
auto function = onnx_import::import_onnx_model(file_util::path_join(CommonTestUtils::getExecutableDirectory(),
SERIALIZED_ZOO,
"onnx/dequantize_linear_4_dynamic.onnx"));
auto test_case = ngraph::test::TestCase(function, s_device);
// The `axis` sttribute is set to 1
// The data input shape in the onnx model is {-1, -1, -1, -1}
test_case.add_input(Shape{2, 3, 2, 4}, std::vector<int8_t>{7, 9, 10, 10, 5, 8, 9, 1, 8, 6, 7, 9, 10, 0, 7, 10, 8,
2, 6, 0, 5, 9, 8, 1, 2, 7, 5, 3, 2, 4, 1, 3, 8, 7,
4, 8, 10, 1, 5, 5, 7, 7, 0, 2, 4, 4, 0, 5}); // x
test_case.add_input(std::vector<float>{1.0f, 10.0f, 7.0f}); // scale
test_case.add_input(std::vector<int8_t>{10, 2, 1}); // zero_point
test_case.add_expected_output<float>(
{2, 3, 2, 4},
std::vector<float>{-3.0f, -1.0f, 0.0f, 0.0f, -5.0f, -2.0f, -1.0f, -9.0f, 60.0f, 40.0f, 50.0f, 70.0f,
80.0f, -20.0f, 50.0f, 80.0f, 49.0f, 7.0f, 35.0f, -7.0f, 28.0f, 56.0f, 49.0f, 0.0f,
-8.0f, -3.0f, -5.0f, -7.0f, -8.0f, -6.0f, -9.0f, -7.0f, 60.0f, 50.0f, 20.0f, 60.0f,
80.0f, -10.0f, 30.0f, 30.0f, 42.0f, 42.0f, -7.0f, 7.0f, 21.0f, 21.0f, -7.0f, 28.0f});
test_case.run();
}
NGRAPH_TEST(${BACKEND_NAME}, onnx_model_dequantize_linear_1d_zero_scale_int8_4d) {
auto function = onnx_import::import_onnx_model(file_util::path_join(CommonTestUtils::getExecutableDirectory(),
SERIALIZED_ZOO,
@@ -276,11 +301,11 @@ NGRAPH_TEST(${BACKEND_NAME}, onnx_model_dequantize_linear_1d_zero_scale_int8_4d)
auto test_case = ngraph::test::TestCase(function, s_device);
test_case.add_input(std::vector<uint8_t>{7, 9, 10, 10, 5, 8, 9, 1, 8, 6, 7, 9, 10, 0, 7, 10,
8, 2, 6, 0, 5, 9, 8, 1, 2, 7, 5, 3, 2, 4, 1, 3,
8, 7, 4, 8, 10, 1, 5, 5, 7, 7, 0, 2, 4, 4, 0, 5}); // x
test_case.add_input(std::vector<float>{1.0f, 10.0f, 7.0f}); // scale
test_case.add_input(std::vector<uint8_t>{10, 2, 1}); // zero_point
test_case.add_input(std::vector<int8_t>{7, 9, 10, 10, 5, 8, 9, 1, 8, 6, 7, 9, 10, 0, 7, 10,
8, 2, 6, 0, 5, 9, 8, 1, 2, 7, 5, 3, 2, 4, 1, 3,
8, 7, 4, 8, 10, 1, 5, 5, 7, 7, 0, 2, 4, 4, 0, 5}); // x
test_case.add_input(std::vector<float>{1.0f, 10.0f, 7.0f}); // scale
test_case.add_input(std::vector<int8_t>{10, 2, 1}); // zero_point
test_case.add_expected_output<float>(
{2, 3, 2, 4},
src/frontends/onnx/tests/runtime/ie/unit_test.manifest
-19
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@@ -10,20 +10,6 @@
#
#-------------------------------------------------------------------------------
# Quantize layer input 'Multiply_7' doesn't have blobs
onnx_model_quantize_linear
onnx_model_quantize_linear_zero_point
onnx_model_quantize_linear_axis_zero
onnx_model_quantize_linear_axis_negative
onnx_expand_function
# DequantizeLinear:
# C++ exception with description "Unsupported precisions!
IE_CPU.onnx_model_dequantize_linear_scalar_zero_scale_int8
IE_CPU.onnx_model_dequantize_linear_1d_zero_scale_int8
# C++ exception with description "Input data precision not supported. Expected float.
IE_CPU.onnx_model_dequantize_linear_1d_zero_scale_int8_4d
# Result mismatch
onnx_model_shape
@@ -101,10 +87,6 @@ onnx_model_erf_int32
# Could not eliminate all Dyn nodes
onnx_model_conv_with_dynamic_batch
# Segmentation fault
onnx_model_fake_quantize_nonconst_inputs_infer
onnx_model_quantize_linear_const_scale_const_zero_p
# OneHot operation has a form that is not supported
onnx_model_one_hot_without_axis
onnx_model_one_hot_with_axis
@@ -433,4 +415,3 @@ IE_CPU.onnx_model_top_k_repeating_unsorted
# Accuracy regression - Ticket 105909
IE_CPU.onnx_model_attention_qkv_hidden_sizes
src/frontends/onnx/tests/runtime/interpreter/unit_test.manifest
-13
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@@ -12,19 +12,6 @@ INTERPRETER.onnx_dyn_shapes_expand_uint16_dyn_shape
# Revise reference implementation
onnx_dyn_model_hardmax
onnx_model_quantize_linear_const_scale_const_zero_p
onnx_model_quantize_linear
onnx_model_quantize_linear_axis_zero
onnx_model_quantize_linear_axis_negative
# Removed opset0 operations
INTERPRETER.onnx_model_dequantize_linear
INTERPRETER.onnx_model_dequantize_linear_scalar_zero_scale_uint8
INTERPRETER.onnx_model_dequantize_linear_scalar_zero_scale_int8
INTERPRETER.onnx_model_dequantize_linear_1d_zero_scale_uint8
INTERPRETER.onnx_model_dequantize_linear_1d_zero_scale_int8
INTERPRETER.onnx_model_dequantize_linear_1d_zero_scale_int8_4d
INTERPRETER.onnx_model_dequantize_linear_1d_zero_scale_uint8_negative_axis
# ONNX evaluate method not implemented for If operator
INTERPRETER.onnx_if_inside_if