mirror of https://github.com/commaai/tinygrad.git
202 lines
7.6 KiB
Python
202 lines
7.6 KiB
Python
import unittest
|
|
from typing import Any, Tuple
|
|
from onnx.backend.base import Backend, BackendRep
|
|
import onnx.backend.test
|
|
import numpy as np
|
|
from tinygrad import Tensor, Device, dtypes
|
|
from tinygrad.helpers import getenv, OSX
|
|
from test.helpers import is_dtype_supported
|
|
|
|
# pip3 install tabulate
|
|
pytest_plugins = 'onnx.backend.test.report',
|
|
|
|
from extra.onnx import get_run_onnx
|
|
|
|
class TinygradModel(BackendRep):
|
|
def __init__(self, run_onnx, input_names):
|
|
super().__init__()
|
|
self.fxn = run_onnx
|
|
self.input_names = input_names
|
|
|
|
def run(self, inputs: Any, **kwargs: Any) -> Tuple[Any, ...]:
|
|
real_inputs = {k:v for k,v in zip(self.input_names, inputs)}
|
|
ret = self.fxn(real_inputs, debug=True)
|
|
return tuple(x.numpy() if isinstance(x, Tensor) else [i.numpy() for i in x] if isinstance(x, list) else np.array(x) for x in ret.values())
|
|
|
|
class TinygradBackend(Backend):
|
|
@classmethod
|
|
def prepare(cls, model, device):
|
|
input_all = [x.name for x in model.graph.input]
|
|
input_initializer = [x.name for x in model.graph.initializer]
|
|
net_feed_input = [x for x in input_all if x not in input_initializer]
|
|
print("prepare", cls, device, net_feed_input)
|
|
run_onnx = get_run_onnx(model)
|
|
return TinygradModel(run_onnx, net_feed_input)
|
|
|
|
@classmethod
|
|
def supports_device(cls, device: str) -> bool:
|
|
# NOTE: this is onnx CPU
|
|
return device == "CPU"
|
|
|
|
backend_test = onnx.backend.test.BackendTest(TinygradBackend, __name__)
|
|
|
|
# no support for reduce with multiply (needs llop)
|
|
backend_test.exclude('test_reduce_prod_*')
|
|
|
|
# TODO figure out why it's returning wrong values, geohotstan's uneducated guess is it's due to imprecision from float64 (double) -> float32
|
|
# see Type Constraints: https://onnx.ai/onnx/operators/onnx_aionnxpreviewtraining_Adam.html#type-constraints
|
|
backend_test.exclude('test_adam_multiple_cpu')
|
|
backend_test.exclude('test_nesterov_momentum_cpu')
|
|
|
|
# about different dtypes
|
|
if not is_dtype_supported(dtypes.float64):
|
|
backend_test.exclude('float64')
|
|
backend_test.exclude('DOUBLE')
|
|
# these have float64 inputs
|
|
backend_test.exclude('test_eyelike_with_dtype_cpu')
|
|
backend_test.exclude('test_reduce_log_sum_exp*')
|
|
backend_test.exclude('test_operator_add*')
|
|
backend_test.exclude('test_einsum_*')
|
|
backend_test.exclude('test_cumsum_*')
|
|
|
|
if not is_dtype_supported(dtypes.float16):
|
|
backend_test.exclude('float16')
|
|
backend_test.exclude('FLOAT16')
|
|
|
|
# dtype cast
|
|
backend_test.exclude('STRING')
|
|
backend_test.exclude('FLOAT8')
|
|
backend_test.exclude('BFLOAT16') # not supported in numpy
|
|
# TODO: fix these with true onnx float16
|
|
backend_test.exclude('to_FLOAT16')
|
|
backend_test.exclude('cast_no_saturate')
|
|
|
|
backend_test.exclude('test_pow_types_int*')
|
|
backend_test.exclude('test_convinteger_*')
|
|
backend_test.exclude('test_matmulinteger_*')
|
|
|
|
# we don't support indexes
|
|
backend_test.exclude('test_nonzero_*')
|
|
|
|
# no support for mod
|
|
backend_test.exclude('test_mod_*')
|
|
|
|
# no boolean ops (2d, 3d, 4d)
|
|
backend_test.exclude('test_bitshift_*')
|
|
|
|
# no string ops
|
|
backend_test.exclude('string')
|
|
backend_test.exclude('test_strnorm_*')
|
|
backend_test.exclude('test_regex_*')
|
|
|
|
# no scatternd gathernd
|
|
backend_test.exclude('test_gathernd_*')
|
|
backend_test.exclude('test_scatternd_*')
|
|
|
|
# no quantize
|
|
backend_test.exclude('test_dynamicquantizelinear_*')
|
|
backend_test.exclude('test_qlinearmatmul_*')
|
|
backend_test.exclude('test_qlinearconv_*')
|
|
backend_test.exclude('test_quantizelinear_*')
|
|
|
|
# no rnn
|
|
backend_test.exclude('test_gru_*')
|
|
backend_test.exclude('test_rnn_*')
|
|
backend_test.exclude('test_lstm_*')
|
|
backend_test.exclude('test_simple_rnn_*')
|
|
|
|
# no control flow
|
|
# control flow uses AttributeProto.GRAPH
|
|
backend_test.exclude('test_if_*')
|
|
backend_test.exclude('test_loop*')
|
|
backend_test.exclude('test_range_float_type_positive_delta_expanded_cpu') # requires loop
|
|
backend_test.exclude('test_affine_grid_2d_align_corners_expanded_cpu')
|
|
backend_test.exclude('test_affine_grid_2d_expanded_cpu')
|
|
backend_test.exclude('test_affine_grid_3d_align_corners_expanded_cpu')
|
|
backend_test.exclude('test_affine_grid_3d_expanded_cpu')
|
|
backend_test.exclude('test_range_int32_type_negative_delta_expanded_cpu')
|
|
|
|
# unsupported (strange) ops
|
|
backend_test.exclude('test_bitwise_*')
|
|
backend_test.exclude('test_blackmanwindow_*')
|
|
backend_test.exclude('test_bernoulli_*')
|
|
backend_test.exclude('test_det_*')
|
|
backend_test.exclude('test_col2im_*')
|
|
backend_test.exclude('test_hammingwindow_*')
|
|
backend_test.exclude('test_hannwindow_*')
|
|
backend_test.exclude('test_hardmax_*')
|
|
backend_test.exclude('test_gridsample_*')
|
|
backend_test.exclude('test_dft_*')
|
|
backend_test.exclude('test_einsum_batch_diagonal_cpu*') # TODO: equation = '...ii ->...i'
|
|
backend_test.exclude('test_einsum_inner_prod_cpu*') # TODO: equation = 'i,i'
|
|
backend_test.exclude('test_unique_*')
|
|
backend_test.exclude('test_sequence_*')
|
|
backend_test.exclude('test_nonmaxsuppression_*')
|
|
backend_test.exclude('test_reversesequence_*')
|
|
backend_test.exclude('test_roialign_*')
|
|
backend_test.exclude('test_top_k_*')
|
|
backend_test.exclude('test_tfidfvectorizer_*')
|
|
backend_test.exclude('test_stft_*')
|
|
backend_test.exclude('test_melweightmatrix_*')
|
|
|
|
# more strange ops
|
|
backend_test.exclude('test_basic_deform_conv_*')
|
|
backend_test.exclude('test_deform_conv_*')
|
|
backend_test.exclude('test_lppool_*')
|
|
backend_test.exclude('test_scan*')
|
|
backend_test.exclude('test_split_to_sequence_*')
|
|
backend_test.exclude('test_resize_downsample_scales_cubic_*') # unsure how to implement cubic
|
|
backend_test.exclude('test_resize_downsample_sizes_cubic_*') # unsure how to implement cubic
|
|
backend_test.exclude('test_resize_upsample_scales_cubic_*') # unsure how to implement cubic
|
|
backend_test.exclude('test_resize_upsample_sizes_cubic_*') # unsure how to implement cubic
|
|
|
|
# rest of the failing tests
|
|
backend_test.exclude('test_resize_downsample_scales_linear_antialias_cpu') # antialias not implemented
|
|
backend_test.exclude('test_resize_downsample_sizes_linear_antialias_cpu') # antialias not implemented
|
|
backend_test.exclude('test_resize_tf_crop_and_resize_cpu') # unsure about fill value after clip
|
|
backend_test.exclude('test_ai_onnx_ml_label_encoder_tensor_value_only_mapping_cpu') # bad data type string
|
|
backend_test.exclude('test_ai_onnx_ml_label_encoder_tensor_mapping_cpu') # bad data type string
|
|
|
|
if Device.DEFAULT in ['GPU', 'METAL']:
|
|
backend_test.exclude('test_resize_upsample_sizes_nearest_axes_2_3_cpu')
|
|
backend_test.exclude('test_resize_upsample_sizes_nearest_axes_3_2_cpu')
|
|
backend_test.exclude('test_resize_upsample_sizes_nearest_cpu')
|
|
|
|
if Device.DEFAULT == "METAL" or (OSX and Device.DEFAULT == "GPU"):
|
|
# numerical inaccuracy
|
|
backend_test.exclude('test_mish_cpu')
|
|
backend_test.exclude('test_mish_expanded_cpu')
|
|
|
|
# TODO: llvm has problems with inf
|
|
if Device.DEFAULT in ['LLVM']:
|
|
backend_test.exclude('test_isinf_cpu')
|
|
backend_test.exclude('test_isinf_negative_cpu')
|
|
backend_test.exclude('test_isinf_positive_cpu')
|
|
|
|
# # TODO: problems with nan
|
|
if Device.DEFAULT in ['LLVM']:
|
|
backend_test.exclude('test_isnan_float16_cpu')
|
|
backend_test.exclude('test_isnan_cpu')
|
|
|
|
# disable model tests for now since they are slow
|
|
if not getenv("MODELTESTS"):
|
|
for x in backend_test.test_suite:
|
|
if 'OnnxBackendRealModelTest' in str(type(x)):
|
|
backend_test.exclude(str(x).split(" ")[0])
|
|
else:
|
|
# model tests all pass!
|
|
backend_test.include('test_resnet50')
|
|
backend_test.include('test_inception_v1')
|
|
backend_test.include('test_inception_v2')
|
|
backend_test.include('test_densenet121')
|
|
backend_test.include('test_shufflenet')
|
|
backend_test.include('test_squeezenet')
|
|
backend_test.include('test_bvlc_alexnet')
|
|
backend_test.include('test_zfnet512')
|
|
backend_test.include('test_vgg19')
|
|
|
|
globals().update(backend_test.enable_report().test_cases)
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|