test_topi_relu.py 2.73 KB
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"""Test code for relu activation"""
import os
import numpy as np
import tvm
import topi
from topi.util import get_const_tuple

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from common import get_all_backend

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def verify_relu(m, n):
    A = tvm.placeholder((m, n), name='A')
    B = topi.nn.relu(A)

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    a_np = np.random.uniform(low=-1.0, high=1.0, size=get_const_tuple(A.shape)).astype(A.dtype)
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    b_np = a_np * (a_np > 0)

    def check_device(device):
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        ctx = tvm.context(device, 0)
        if not ctx.exist:
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            print("Skip because %s is not enabled" % device)
            return
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        print("Running on target: %s" % device)
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        with tvm.target.create(device):
            s = topi.generic.schedule_elemwise(B)
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        a = tvm.nd.array(a_np, ctx)
        b = tvm.nd.array(np.zeros(get_const_tuple(B.shape), dtype=B.dtype), ctx)
        foo = tvm.build(s, [A, B], device, name="relu")
        foo(a, b)
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        tvm.testing.assert_allclose(b.asnumpy(), b_np, rtol=1e-5)
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    for device in get_all_backend():
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        check_device(device)

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def verify_leaky_relu(m, alpha):
    A = tvm.placeholder((m,), name='A')
    B = topi.nn.leaky_relu(A, alpha)
    s = tvm.create_schedule([B.op])

    a_np = np.random.uniform(size=get_const_tuple(A.shape)).astype(A.dtype)
    b_np = a_np * (a_np > 0) + a_np * (a_np < 0) * alpha
    ctx = tvm.cpu(0)
    a = tvm.nd.array(a_np, ctx)
    b = tvm.nd.array(np.zeros(get_const_tuple(B.shape), dtype=B.dtype), ctx)
    foo = tvm.build(s, [A, B], "llvm", name="leaky_relu")
    foo(a, b)
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    tvm.testing.assert_allclose(b.asnumpy(), b_np, rtol=1e-5)
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def verify_prelu(x, w, axis, weight_reshape):
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    X = tvm.placeholder((x), name='X')
    W = tvm.placeholder((w), name='W')
    x_np = np.random.uniform(low=-1.0, high=1.0, size=get_const_tuple(X.shape)).astype(X.dtype)
    w_np = np.random.uniform(low=-1.0, high=1.0, size=get_const_tuple(W.shape)).astype(W.dtype)

    def _prelu_numpy(x, W):
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        return (x < 0) * (x *W.reshape(weight_reshape)) + (x>=0) * x
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    B = topi.nn.prelu(X, W, axis)
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    s = tvm.create_schedule([B.op])

    ctx = tvm.cpu(0)
    x_tvm = tvm.nd.array(x_np, ctx)
    w_tvm = tvm.nd.array(w_np, ctx)

    b = tvm.nd.array(np.zeros(get_const_tuple(X.shape), dtype=B.dtype), ctx)
    foo = tvm.build(s, [X, W, B], "llvm", name="prelu")
    foo(x_tvm, w_tvm, b)
    out_np = _prelu_numpy(x_np, w_np)
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    tvm.testing.assert_allclose(b.asnumpy(), out_np, rtol=1e-5)
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def test_relu():
    verify_relu(10, 128)

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def test_schedule_big_array():
    verify_relu(1024 * 100 , 512)


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def test_leaky_relu():
    verify_leaky_relu(100, 0.1)

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def test_prelu():
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    verify_prelu((1, 3, 2, 2), (3,), 1, (3, 1, 1))
    verify_prelu((1, 3, 2, 2), (2,), 2, (2, 1))
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if __name__ == "__main__":
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    test_schedule_big_array()
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    test_relu()
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    test_leaky_relu()
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    test_prelu()