Files
tinygrad/test/external/external_test_onnx_backend.py
geohotstan 9af5645ba3 onnx full passing (#1076)
* 1

* 83 failed

* learning how git works

* lol idk

* zero shape aaaa

* space lol

* aaa

* test check

* haha

* fixed gather

* 73 failing

* 71 failing

* 68 failing

* added some debug

* fking resize

* lol

* 62 failing

* 58 failling fucking did nearest resize hell yeah

* clean up

* 56 failing

* janitor duty

* lol

* 53 failing

* hi mom

* 50 failing

* added linear interp, but coord_trans is wrong

* did lin interpolation woohoo

* 43 failing

* 40 failing

* temporary Gather fix

* 39 failing

* fixed slice onnxver<10

* 37 failing

* 35 failing

* excluded tests that use float64

* 32 failing with hacks

* added _batchnorm() for 3D 5D batchnorm, 29 failing

* changed ALLOWED_KERNEL_COUNT from 199 to 207

* added improved Gather op, reverted ALLOWED_KERNEL_COUNT commit

* support Round op

* added storage_order/indices maxpool, 27 failing

* support maxunpool, 25 failures

* support Gradient, 23 failures

* merged new where

* added Adam

* cleanups

* added Momentum and Nesterov Momentum

* added Adagrad

* support sequence_type, 20 failing

* ugh git

* I give up on cubic interp :D, 9 failing

* sexy 1 liner gather, much improved, wow

* polished gather to make it shine bright like a diamond

* clean 1 liner for gather

* improved readability of gather

* uhh

* clean up

* more clean up

* WHITEspace

* implemented SoftmaxCrossEntropyLoss op

* added comments and cleaned up if statements

* update

* thank based wozeparrot for pow and new GatherElements

* CPU and TORCH all pass | cast float64 -> float32 for all fromCPU()

* _nearest_gather() failing on yolo

* reverted ops_cpu change and added assert in Resize

* added comments for resize for multiple channels

* oops

* merge

* test

* switched np.pad to Tensor.pad for constant padding

* gah

* gah2

* sexy reflect pad with movementops -> add

* delete commented out lines

* edge mode pad sexy as well

* trying out model_benchmark

* revert gitignore change lol

* init

* Revert "init"

This reverts commit 682bf2073a.

* wrote cast workaround for CPU, CPU and TORCH all pass

* wrote cast workaround for CPU, CPU and TORCH all pass

* skipped tests w/ 0 shape for METAL and GPU

* excluded tests for CLANG, CPU, TORCH, CLANG pass

* fixed hacky ConvTranspose

* gotta figure out autopad

* UOps.STORE support cast bool -> float

* small fix for fast gather

* reverted 0 shape skipped tests

* oops missed a file

* added comment

* fixed slice op hack

* First commit to pr

* More trig ops

* More trig ops

* format

* isinf support

* More ops

* changed onnx_ops to use our new gather :D

* Det op bug fix

* rebase

* fixed some tests

* det broken and slow

* fixed compress to use new gather

* implemented argmax argmin

* support variable types in type_proto

* support Upsample and Identity sequence

* we support float64 now and tinygrad support automatic broadcasting

* added EyeLike op

* resize does support multiple channels now actually

* yolov8 onnx runs successfully

* added batch size 1

* oops

* finally fixed type_proto I think

* fixed some llvm bugs

* del whitespaces

* added ZenginU Format PR

* test

* oops

* added float64 exclude tests back

* more skipped tests

* try

* ok openpilot pass

* flake8 pass

* woooooohooo

* revert external_model_benchmark changes

* perf tested gather

* removed promote types from ops_cpu

* numerical errors from 1681 is fixed

---------

Co-authored-by: ZenginU <umutzengin00@gmail.com>
2023-09-05 13:23:32 -07:00

236 lines
9.6 KiB
Python

import unittest
from onnx.backend.base import Backend, BackendRep
import onnx.backend.test
import numpy as np
from tinygrad.tensor import Tensor
from typing import Any, Tuple
from tinygrad.helpers import getenv
# 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:
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')
# we only support float32
backend_test.exclude('uint8')
backend_test.exclude('uint16')
backend_test.exclude('uint32')
backend_test.exclude('uint64')
backend_test.exclude('int8')
backend_test.exclude('int16')
backend_test.exclude('float64')
backend_test.exclude('string')
backend_test.exclude('test_pow_types_int*')
backend_test.exclude('test_cast_*')
backend_test.exclude('test_castlike_*')
backend_test.exclude('test_convinteger_*')
backend_test.exclude('test_matmulinteger_*')
backend_test.exclude('test_reduce_log_sum_exp*') # dependent on actual float64 implementation for backends
backend_test.exclude('test_operator_add*') # dependent on float64 math. Without it values default to 0 or inf
# we don't support indexes
# backend_test.exclude('test_argmax_*') # Needs more work #select_last_index
# backend_test.exclude('test_argmin_*') # Needs more work #select_last_index
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 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
backend_test.exclude('test_if_*')
backend_test.exclude('test_loop*')
backend_test.exclude('test_range_float_type_positive_delta_expanded_cpu') # requires loop
# unsupported (strange) ops
backend_test.exclude('test_bitwise_*')
backend_test.exclude('test_blackmanwindow_*')
backend_test.exclude('test_bernoulli_*')
backend_test.exclude('test_cumsum_*')
backend_test.exclude('test_det_*')
backend_test.exclude('test_tril_zero_cpu') # TODO: zero array support
backend_test.exclude('test_triu_zero_cpu') # TODO: zero array support
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_*')
backend_test.exclude('test_strnorm_*')
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_depthtospace_*')
backend_test.exclude('test_spacetodepth_*')
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_averagepool_2d_dilations_cpu') # dilations != 1 not supported for avgpool
backend_test.exclude('test_convtranspose_autopad_same_cpu') # TODO geohotstan has no idea how this is done, autopad requires output_shape but output_shape requires pads from autopad
backend_test.exclude('test_optional_has_element_empty_optional_input_cpu') # Attempts to create Tensor from None
backend_test.exclude('test_range_int32_type_negative_delta_expanded_cpu') # AttributeProto.GRAPH not implemented
backend_test.exclude('test_reshape_allowzero_reordered_cpu') # reshaping to 0 shape
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_operator_addconstant_cpu') # bad data type
# 1556
backend_test.exclude('test_isinf_cpu')
backend_test.exclude('test_isinf_negative_cpu')
backend_test.exclude('test_isinf_positive_cpu')
backend_test.exclude('test_isnan_cpu')
if getenv("CPU") or getenv("ARM64"):
# not too sure
backend_test.exclude('test_dequantizelinear_axis_cpu')
backend_test.exclude('test_dequantizelinear_cpu')
if getenv("TORCH"): # 1562
backend_test.exclude('test_and2d_cpu')
backend_test.exclude('test_and3d_cpu')
backend_test.exclude('test_and4d_cpu')
backend_test.exclude('test_and_bcast3v1d_cpu')
backend_test.exclude('test_and_bcast3v2d_cpu')
backend_test.exclude('test_and_bcast4v2d_cpu')
backend_test.exclude('test_and_bcast4v3d_cpu')
backend_test.exclude('test_and_bcast4v4d_cpu')
backend_test.exclude('test_dequantizelinear_axis_cpu')
backend_test.exclude('test_dequantizelinear_cpu')
backend_test.exclude('test_greater_equal_bcast_expanded_cpu')
backend_test.exclude('test_greater_equal_expanded_cpu')
backend_test.exclude('test_isinf_cpu')
backend_test.exclude('test_isinf_negative_cpu')
backend_test.exclude('test_isinf_positive_cpu')
backend_test.exclude('test_isnan_cpu')
backend_test.exclude('test_less_equal_bcast_expanded_cpu')
backend_test.exclude('test_less_equal_expanded_cpu')
backend_test.exclude('test_or2d_cpu')
backend_test.exclude('test_or3d_cpu')
backend_test.exclude('test_or4d_cpu')
backend_test.exclude('test_or_bcast3v1d_cpu')
backend_test.exclude('test_or_bcast3v2d_cpu')
backend_test.exclude('test_or_bcast4v2d_cpu')
backend_test.exclude('test_or_bcast4v3d_cpu')
backend_test.exclude('test_or_bcast4v4d_cpu')
backend_test.exclude('test_xor2d_cpu')
backend_test.exclude('test_xor3d_cpu')
backend_test.exclude('test_xor4d_cpu')
backend_test.exclude('test_xor_bcast3v1d_cpu')
backend_test.exclude('test_xor_bcast3v2d_cpu')
backend_test.exclude('test_xor_bcast4v2d_cpu')
backend_test.exclude('test_xor_bcast4v3d_cpu')
backend_test.exclude('test_xor_bcast4v4d_cpu')
if getenv('LLVM') or getenv('GPU') or getenv('CLANG') or getenv('METAL') or getenv('MPS'):
# compiled backends cannot reshape to 0 or from 0
backend_test.exclude('test_slice_start_out_of_bounds_cpu')
backend_test.exclude('test_constantofshape_int_shape_zero_cpu')
if getenv('GPU') or getenv('METAL') or getenv('MPS'):
backend_test.exclude('test_mish_cpu') # weird inaccuracy
backend_test.exclude('test_mish_expanded_cpu') # weird inaccuracy
backend_test.exclude('test_eyelike_with_dtype_cpu') # I'm not sure about this...
if getenv('METAL') or getenv('MPS'):
# (((Tensor([0,1,2,3,4,5])+0.5)/3.5 - 0.5)) Try this with METAL and LLVM, weird weird inaccuracy
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')
# 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()