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[CMSIS-NN] Initial operator support for Mul
This is largely as it says on the tin, it adds Mul support to CMSIS-NN
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# Licensed to the Apache Software Foundation (ASF) under one | ||
# or more contributor license agreements. See the NOTICE file | ||
# distributed with this work for additional information | ||
# regarding copyright ownership. The ASF licenses this file | ||
# to you under the Apache License, Version 2.0 (the | ||
# "License"); you may not use this file except in compliance | ||
# with the License. You may obtain a copy of the License at | ||
# | ||
# http://www.apache.org/licenses/LICENSE-2.0 | ||
# | ||
# Unless required by applicable law or agreed to in writing, | ||
# software distributed under the License is distributed on an | ||
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
# KIND, either express or implied. See the License for the | ||
# specific language governing permissions and limitations | ||
# under the License. | ||
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"""CMSIS-NN integration tests: mul""" | ||
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import sys | ||
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import numpy as np | ||
import pytest | ||
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from tvm import relay | ||
from tvm.relay.op.contrib import cmsisnn | ||
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from utils import skip_if_no_reference_system, make_module, count_num_calls, get_range_for_dtype_str | ||
from tests.python.relay.aot.aot_test_utils import ( | ||
AOTTestModel, | ||
AOT_CORSTONE300_RUNNER, | ||
generate_ref_data, | ||
compile_and_run, | ||
) | ||
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def make_model( | ||
shape, | ||
input_0_dtype, | ||
input_1_dtype, | ||
input_0_scale, | ||
input_0_zero_point, | ||
input_1_scale, | ||
input_1_zero_point, | ||
out_scale=1.0 / 256, | ||
out_zero_point=-128, | ||
): | ||
"""Create a Relay Function / network model""" | ||
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return relay.qnn.op.mul( | ||
relay.var("input_0", shape=shape, dtype=input_0_dtype), | ||
relay.var("input_1", shape=shape, dtype=input_1_dtype), | ||
relay.const(input_0_scale, "float32"), | ||
relay.const(input_0_zero_point, "int32"), | ||
relay.const(input_1_scale, "float32"), | ||
relay.const(input_1_zero_point, "int32"), | ||
relay.const(out_scale, "float32"), | ||
relay.const(out_zero_point, "int32"), | ||
) | ||
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@skip_if_no_reference_system | ||
@pytest.mark.parametrize( | ||
[ | ||
"input_0_scale", | ||
"input_0_zero_point", | ||
"input_1_scale", | ||
"input_1_zero_point", | ||
"output_tolerance", | ||
], | ||
[[0.256, 33, 0.256, 33, 0], [0.0128, -64, 0.0128, -64, 1], [0.0128, -64, 0.256, 33, 0]], | ||
) | ||
def test_mul_int8( | ||
input_0_scale, input_0_zero_point, input_1_scale, input_1_zero_point, output_tolerance | ||
): | ||
interface_api = "c" | ||
use_unpacked_api = True | ||
test_runner = AOT_CORSTONE300_RUNNER | ||
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dtype = "int8" | ||
shape = [1, 16, 16, 3] | ||
model = make_model( | ||
shape, dtype, dtype, input_0_scale, input_0_zero_point, input_1_scale, input_1_zero_point | ||
) | ||
orig_mod = make_module(model) | ||
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cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod) | ||
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# validate pattern matching | ||
attrs = [ | ||
cmsisnn_mod[var.name_hint].attrs | ||
for var in cmsisnn_mod.get_global_vars() | ||
if cmsisnn_mod[var.name_hint].attrs | ||
] | ||
assert any(attrs), "At least one function with external attributes was expected." | ||
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compilers = [ | ||
key == "Compiler" and value == "cmsisnn" for attr in attrs for key, value in attr.items() | ||
] | ||
assert any(compilers), "Module does not contain function for cmsisnn target." | ||
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assert count_num_calls(orig_mod) == count_num_calls( | ||
cmsisnn_mod | ||
), "Number of calls changed during partitioning" | ||
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# validate the output | ||
in_min, in_max = get_range_for_dtype_str(dtype) | ||
inputs = { | ||
"input_0": np.random.randint(in_min, high=in_max, size=shape, dtype=dtype), | ||
"input_1": np.random.randint(in_min, high=in_max, size=shape, dtype=dtype), | ||
} | ||
output_list = generate_ref_data(orig_mod["main"], inputs) | ||
compile_and_run( | ||
AOTTestModel( | ||
module=cmsisnn_mod, | ||
inputs=inputs, | ||
outputs=output_list, | ||
output_tolerance=output_tolerance, | ||
), | ||
test_runner, | ||
interface_api, | ||
use_unpacked_api, | ||
) | ||
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@pytest.mark.parametrize(["input_dtype"], [["uint8"], ["int16"]]) | ||
def test_invalid_parameters( | ||
input_dtype, | ||
): | ||
input_scale = 0.256 | ||
input_zero_point = 33 | ||
model = make_model( | ||
[1, 16, 16, 3], | ||
input_dtype, | ||
input_dtype, | ||
input_scale, | ||
input_zero_point, | ||
input_scale, | ||
input_zero_point, | ||
) | ||
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orig_mod = make_module(model) | ||
cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod) | ||
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attrs = [ | ||
cmsisnn_mod[var.name_hint].attrs | ||
for var in cmsisnn_mod.get_global_vars() | ||
if cmsisnn_mod[var.name_hint].attrs | ||
] | ||
assert not any(attrs), "No function should have an external attribute." | ||
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if __name__ == "__main__": | ||
sys.exit(pytest.main([__file__] + sys.argv[1:])) |
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