72 строки
2.7 KiB
Python
72 строки
2.7 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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"""Test code for binary neural network operators."""
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import numpy as np
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import tvm
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import topi
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from topi.util import get_const_tuple
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from tvm.contrib.pickle_memoize import memoize
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def verify_binary_dense(batch, in_dim, out_dim):
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A = tvm.placeholder((batch, in_dim), name='A')
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B = tvm.placeholder((out_dim, in_dim), name='B')
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bnn_A = topi.nn.binarize_pack(A)
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bnn_B = topi.nn.binarize_pack(B)
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# binary dense
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bnn_A1 = tvm.placeholder(bnn_A.shape, dtype=bnn_A.dtype)
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bnn_B1 = tvm.placeholder(bnn_B.shape, dtype=bnn_B.dtype)
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bnn_C = topi.nn.binary_dense(bnn_A1, bnn_B1)
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# schedule
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with tvm.target.create('llvm'):
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s1 = topi.generic.schedule_binarize_pack(bnn_A)
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s2 = topi.generic.schedule_binarize_pack(bnn_B)
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s3 = topi.generic.schedule_binary_dense(bnn_C)
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dtype = A.dtype
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@memoize("topi.tests.test_topi_binary_dense")
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def get_ref_data():
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# generate random matrix of +1 or -1 value
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a_np = (np.random.randint(2, size=(batch, in_dim)) * 2 - 1).astype(dtype)
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b_np = (np.random.randint(2, size=(out_dim, in_dim)) * 2 - 1).astype(dtype)
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c_np = np.dot(a_np, b_np.T)
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return a_np, b_np, c_np
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a_np, b_np, c_np = get_ref_data()
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ctx = tvm.cpu(0)
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a = tvm.nd.array(a_np, ctx)
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b = tvm.nd.array(b_np, ctx)
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bnn_a = tvm.nd.array(np.zeros(get_const_tuple(bnn_A.shape), dtype=bnn_A.dtype), ctx)
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bnn_b = tvm.nd.array(np.zeros(get_const_tuple(bnn_B.shape), dtype=bnn_B.dtype), ctx)
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bnn_c = tvm.nd.array(np.zeros(get_const_tuple(bnn_C.shape), dtype=bnn_C.dtype), ctx)
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f1 = tvm.build(s1, [A, bnn_A], 'llvm')
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f2 = tvm.build(s2, [B, bnn_B], 'llvm')
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f3 = tvm.build(s3, [bnn_A1, bnn_B1, bnn_C], 'llvm')
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f1(a, bnn_a)
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f2(b, bnn_b)
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f3(bnn_a, bnn_b, bnn_c)
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tvm.testing.assert_allclose(bnn_c.asnumpy(), c_np, rtol=1e-5)
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def test_binary_dense():
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verify_binary_dense(1, 4096, 1024)
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verify_binary_dense(1, 1024, 1000)
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if __name__ == "__main__":
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test_binary_dense()
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