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inference_backend.py
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inference_backend.py
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#!/usr/bin/env python3
##################### inference_backend.py #####################################
#
# Copyright 2021, 2024 The IBM Research Authors.
#
################################################################################
from __future__ import absolute_import
from __future__ import annotations
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import os
import sys
import warnings
import json
import base64
import numpy as np
import re
import onnx
import onnx.parser
import subprocess
from onnx.backend.base import Device, DeviceType, Backend
from onnx.backend.test import BackendTest
from onnx import numpy_helper
import variables
from variables import *
from common import compile_model
from onnxmlir_node_tests import load_onnxmlir_node_tests
from typing import Sequence, Any
def get_test_models():
# Test directories:
# https://github.com/onnx/onnx/tree/main/onnx/backend/test/data/node
# In our directories, the python files that generate the tests are found here
# onnx-mlir/third_party/onnx/onnx/backend/test/case/node
# For your convenience, all the test cases can be found in file:
# ./all_test_names.txt
# Each benchmark is defined by a dictionary element: `key:value`, where
# - key: the ONNX testname
# - value: a dictionary accepting only three key "static", "dynamic", and
# "constant" to enable testings for static, dynamic, and constant
# inputs, respectively.
# When a dynamic or constant testing is enabled, we must enter the indices of
# the tensor expected to be dynamic or constant.
# Indices start from 0. -1 means all inputs or all dimensions.
#
# Value for "static" key is not taken into account. So empty set {} is O.K.
#
# Value for "dynamic" key is a dict to define which inputs/dimensions are changed
# to unknown, where its key is an input index and its value is a set of
# dimension indices, e.g. {0:{0,1}, 1:{-1}, 2:{0}}
#
# Value for "constant" key is set of indices, e.g. {0, 2, 3}
# ADDING NEW TESTS / OPS
#
# * Please add new ops in the order they are found in
# onnx-mlir/third_party/onnx/onnx/backend/test/case/node
# * Please add individual tests in the order they are found in the file.
# Most have been properly ordered, some are still not. Please fix as you
# make changes
#
#
# SEMANTIC for LABELING (one line per directive)
# see utils/genSupportedOps.py
# command processed by makefile `make onnx_mlir_supported_ops_cpu`
variables.node_test_to_enable_dict = {
############################################################
# Elementary ops, ordered in the order they are found in
# onnx-mlir/third_party/onnx/onnx/backend/test/case/node.
# ==ARCH== cpu
# ==OP== Abs
# ==MIN== 6
"test_abs_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Acos
# ==MIN== 7
"test_acos_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_acos_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Acosh
# ==MIN== 9
"test_acosh_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_acosh_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Add
# ==MIN== 6
# ==LIM== No support for short integers.
"test_add_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_add_bcast_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# "test_add_uint8_cpu" : {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
# ==OP== And
# ==MIN== 7
"test_and2d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_and3d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_and4d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_and_bcast3v1d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_and_bcast3v2d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_and_bcast4v2d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_and_bcast4v3d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_and_bcast4v4d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== ArgMax
# ==MIN== 1
"test_argmax_no_keepdims_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_argmax_keepdims_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_argmax_default_axis_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_argmax_no_keepdims_random_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_argmax_keepdims_random_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_argmax_default_axis_random_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== ArgMin
# ==MIN== 13
"test_argmin_no_keepdims_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_argmin_keepdims_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_argmin_default_axis_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_argmin_no_keepdims_random_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_argmin_keepdims_random_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_argmin_default_axis_random_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Asin
# ==MIN== 7
"test_asin_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_asin_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Asinh
# ==MIN== 9
"test_asinh_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_asinh_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Atan
# ==MIN== 7
"test_atan_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_atan_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Atanh
# ==MIN== 9
"test_atanh_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_atanh_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== AveragePool
# ==MIN== 1
# TODO: original comment stated "same_upper/lower with dynamic padding-shapes not supported."
# However, I see the dyn shape test being done on all tests, including same_upper. So I am
# assuming that this comment is outdated.
"test_averagepool_1d_default_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_averagepool_2d_ceil_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_averagepool_2d_default_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_averagepool_2d_pads_count_include_pad_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_averagepool_2d_pads_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_averagepool_2d_precomputed_pads_count_include_pad_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_averagepool_2d_precomputed_pads_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_averagepool_2d_precomputed_same_upper_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_averagepool_2d_precomputed_strides_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_averagepool_2d_same_lower_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_averagepool_2d_same_upper_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_averagepool_2d_strides_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_averagepool_3d_default_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== BatchNormalization
# ==MIN== 6
# ==LIM== Training not supported.
"test_batchnorm_epsilon_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_batchnorm_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== BitwiseAnd
# ==MIN== 18
"test_bitwise_and_i32_2d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_bitwise_and_i16_3d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== BitwiseOr
# ==MIN== 18
"test_bitwise_or_i32_2d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_bitwise_or_i16_4d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== BitwiseXor
# ==MIN== 18
"test_bitwise_xor_i32_2d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_bitwise_xor_i16_3d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Cast
# ==MIN== 6
# ==LIM== Cast only between float and double types. Only ppc64le and MacOS platforms support float16. Does not support int4 and uint4.
"test_cast_FLOAT_to_DOUBLE_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_cast_DOUBLE_to_FLOAT_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_cast_FLOAT_to_FLOAT16_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
FLOAT16: {},
},
"test_cast_FLOAT16_to_FLOAT_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
FLOAT16: {},
},
"test_cast_FLOAT16_to_DOUBLE_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
FLOAT16: {},
},
"test_cast_DOUBLE_to_FLOAT16_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
FLOAT16: {},
},
"test_cast_FLOAT_to_STRING_cpu": {}, # appears unsupported at this time
"test_cast_STRING_to_FLOAT_cpu": {}, # appears unsupported at this time
# ==OP== CastLike
# ==MIN== 19
# ==LIM== CastLike only between float and double types. Only ppc64le and MacOS platforms support float16. Does not support int4 and uint4.
"test_castlike_FLOAT_to_DOUBLE_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_castlike_DOUBLE_to_FLOAT_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_castlike_FLOAT_to_FLOAT16_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
FLOAT16: {},
},
"test_castlike_FLOAT16_to_FLOAT_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
FLOAT16: {},
},
"test_castlike_FLOAT16_to_DOUBLE_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
FLOAT16: {},
},
"test_castlike_DOUBLE_to_FLOAT16_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
FLOAT16: {},
},
"test_castlike_FLOAT_to_STRING_cpu": {}, # appears unsupported at this time
"test_castlike_STRING_to_FLOAT_cpu": {}, # appears unsupported at this time
# ==OP== Ceil
# ==MIN== 6
"test_ceil_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_ceil_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Clip
# ==MIN== 6
# ==LIM== No support for short integers
"test_clip_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_clip_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_clip_inbounds_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_clip_outbounds_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_clip_splitbounds_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_clip_default_min_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_clip_default_max_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_clip_default_inbounds_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# "test_clip_default_int8_min_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}},
# "test_clip_default_int8_max_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}},
# "test_clip_default_int8_inbounds_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}},
# ==OP== Compress
# ==MIN== 9
"test_compress_0_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_compress_1_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_compress_default_axis_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_compress_negative_axis_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Concat
# ==MIN== 4
"test_concat_1d_axis_0_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_concat_2d_axis_0_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_concat_2d_axis_1_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_concat_3d_axis_0_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_concat_3d_axis_1_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_concat_3d_axis_2_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_concat_1d_axis_negative_1_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_concat_2d_axis_negative_1_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_concat_2d_axis_negative_2_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_concat_3d_axis_negative_1_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_concat_3d_axis_negative_2_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_concat_3d_axis_negative_3_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Constant
# ==MIN== 1
# ==LIM== Does not support int4 and uint4.
# By def, no dynamic shapes.
"test_constant_cpu": {STATIC_SHAPE: {}},
# ==OP== ConstantOfShape
# ==MIN== 9
# ==LIM== Does not support int4 and uint4.
# By def, no dynamic shapes.
"test_constantofshape_float_ones_cpu": {STATIC_SHAPE: {}},
"test_constantofshape_int_zeros_cpu": {STATIC_SHAPE: {}},
# TODO: test below fail with JNI tests
# "test_constantofshape_int_shape_zero_cpu": {STATIC_SHAPE:{}},
# ==OP== Conv
# ==MIN== 1
# CONSTANT_INPUT for weight only. No need to make a restriction.
"test_basic_conv_with_padding_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {1},
},
"test_basic_conv_without_padding_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {1},
},
"test_conv_with_autopad_same_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {1},
},
"test_conv_with_strides_no_padding_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {1},
},
"test_conv_with_strides_padding_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {1},
},
"test_conv_with_strides_and_asymmetric_padding_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {1},
},
# ==OP== ConvTranspose
# ==MIN== 1
# ==LIM== Spatial dimensions (H and W in input `X`, and kH and kW in input `W`) must be static dimension.
"test_convtranspose_1d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {0: {0, 1}, 1: {0, 1}},
CONSTANT_INPUT: {1},
},
"test_convtranspose_3d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {0: {0, 1}, 1: {0, 1}},
CONSTANT_INPUT: {1},
},
"test_convtranspose_autopad_same_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {0: {0, 1}, 1: {0, 1}},
CONSTANT_INPUT: {1},
},
"test_convtranspose_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {0: {0, 1}, 1: {0, 1}},
CONSTANT_INPUT: {1},
},
"test_convtranspose_dilations_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {0: {0, 1}, 1: {0, 1}},
CONSTANT_INPUT: {1},
},
"test_convtranspose_kernel_shape_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {0: {0, 1}, 1: {0, 1}},
CONSTANT_INPUT: {1},
},
"test_convtranspose_output_shape_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {0: {0, 1}, 1: {0, 1}},
CONSTANT_INPUT: {1},
},
"test_convtranspose_pad_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {0: {0, 1}, 1: {0, 1}},
CONSTANT_INPUT: {1},
},
"test_convtranspose_pads_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {0: {0, 1}, 1: {0, 1}},
CONSTANT_INPUT: {1},
},
# ==OP== Cos
# ==MIN== 7
"test_cos_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_cos_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Cosh
# ==MIN== 9
"test_cosh_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_cosh_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== CumSum
# ==MIN== 11
"test_cumsum_1d_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_cumsum_1d_exclusive_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_cumsum_1d_reverse_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_cumsum_1d_reverse_exclusive_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_cumsum_2d_axis_0_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_cumsum_2d_axis_1_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_cumsum_2d_negative_axis_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== DFT
# ==MIN== 17
# "test_dft_axis_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
# "test_dft_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
# "test_dft_inverse_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
# "test_dft_axis_opset19_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
# "test_dft_opset19_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
# "test_dft_inverse_opset19_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
# ==OP== DepthToSpace
# ==MIN== 13
"test_depthtospace_example_cpu": {
STATIC_SHAPE: {},
# Issue #2639: Dynamic test fails. Need to be fixed.
# DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_depthtospace_crd_mode_example_cpu": {
STATIC_SHAPE: {},
# Issue #2639: Dynamic test fails. Need to be fixed.
# DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== DequantizeLinear
# ==MIN== 10
# ==LIM== Only support for per-tensor or layer dequantization. No support for per-axis dequantization. Does not support int4 and uint4.
# "test_dequantizelinear_axis_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
"test_dequantizelinear_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Div
# ==MIN== 6
# ==LIM== No support for short integers.
"test_div_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_div_bcast_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_div_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# "test_div_uint8_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}, CONSTANT_INPUT:{-1}},
# ==OP== Dropout
# ==MIN== 6
# ==LIM== Does not support masked and training.
"test_dropout_default_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_dropout_default_ratio_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# Other dropout test case failed: implementation is missing
# mask is not supported for inference
# "test_dropout_default_mask_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}},
# "test_dropout_default_mask_ratio_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}},
# Error: input arrays contain a mixture of endianness configuration
# "test_training_dropout_default_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}},
# "test_training_dropout_default_mask_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}},
# Error: input arrays contain a mixture of endianness configuration
# "test_training_dropout_default_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}},
# "test_training_dropout_mask_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}},
# Error: input arrays contain a mixture of endianness configuration
# "test_training_dropout_zero_ratio_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}},
# "test_training_dropout_zero_ratio_mask_cpu": {STATIC_SHAPE:{}, DYNAMIC_SHAPE:{-1:{-1}}},
# ==OP== DynamicQuantizeLinear
# ==MIN== 11
"test_dynamicquantizelinear_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_dynamicquantizelinear_expanded_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_dynamicquantizelinear_max_adjusted_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_dynamicquantizelinear_max_adjusted_expanded_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_dynamicquantizelinear_min_adjusted_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_dynamicquantizelinear_min_adjusted_expanded_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Einsum
# ==MIN== 12
# ==LIM== Limited to the types supported by ReduceSum and MatMul (which we decompose to in most cases) which exclude integers with width < 32. `inputs` must have static dimensions.
"test_einsum_batch_diagonal_cpu": {
STATIC_SHAPE: {},
# Issue #2639: Dynamic test fails. Need to be fixed.
# DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_einsum_batch_matmul_cpu": {
STATIC_SHAPE: {},
# Issue #2639: Dynamic test fails. Need to be fixed.
# DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_einsum_inner_prod_cpu": {
STATIC_SHAPE: {},
# Issue #2639: Dynamic test fails. Need to be fixed.
# DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_einsum_sum_cpu": {
STATIC_SHAPE: {},
# Issue #2639: Dynamic test fails. Need to be fixed.
# DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_einsum_transpose_cpu": {
STATIC_SHAPE: {},
# Issue #2639: Dynamic test fails. Need to be fixed.
# DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Elu
# ==MIN== 6
"test_elu_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_elu_default_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_elu_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Equal
# ==MIN== 7
"test_equal_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_equal_bcast_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# Issue #2416: We currently do not support input type of string for backend tests with JNI
"test_equal_string_broadcast_cpu": {
STATIC_SHAPE_STRING: {},
DYNAMIC_SHAPE_STRING: {-1: {-1}},
CONSTANT_INPUT_STRING: {-1},
},
"test_equal_string_cpu": {
STATIC_SHAPE_STRING: {},
DYNAMIC_SHAPE_STRING: {-1: {-1}},
CONSTANT_INPUT_STRING: {-1},
},
# ==OP== Erf
# ==MIN== 9
"test_erf_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Exp
# ==MIN== 6
"test_exp_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_exp_example_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Expand
# ==MIN== 8
# ==LIM== Input `shape` must have static shape.
"test_expand_dim_changed_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {0: {-1}},
CONSTANT_INPUT: {-1},
},
"test_expand_dim_unchanged_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {0: {-1}},
CONSTANT_INPUT: {-1},
},
# ==OP== Flatten
# ==MIN== 1
# ==LIM== Does not support int4 and uint4.
"test_flatten_axis0_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_flatten_axis1_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},
},
"test_flatten_axis2_cpu": {
STATIC_SHAPE: {},
DYNAMIC_SHAPE: {-1: {-1}},
CONSTANT_INPUT: {-1},