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# to you under the Apache License, Version 2.0 (the
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# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
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import tvm
import tvm.testing
from tvm import te
from tvm.contrib import miopen
import numpy as np
@tvm.testing.requires_rocm
def test_conv2d():
in_channel = 3
out_channel = 64
filter_h = 3
filter_w = 3
pad_h = 1
pad_w = 1
stride_h = 1
stride_w = 1
dilation_h = 1
dilation_w = 1
xshape = [1, in_channel, 128, 128]
if not tvm.get_global_func("tvm.contrib.miopen.conv2d.setup", True):
print("skip because miopen is not enabled...")
return
wshape = (out_channel, in_channel, filter_h, filter_w)
X = te.placeholder(xshape, name="X")
W = te.placeholder(wshape, name="W")
Y = miopen.conv2d_forward(
X, W, stride_h, stride_w, pad_h, pad_w, dilation_h, dilation_w, conv_mode=0, data_type=1
)
yshape = [x.value for x in Y.shape]
from tvm import topi
s = te.create_schedule(Y.op)
def verify():
ctx = tvm.rocm(0)
f = tvm.build(s, [X, W, Y], "rocm", target_host="llvm", name="conv2d")
x = tvm.nd.array(np.random.uniform(-1, 1, xshape).astype(np.float32), ctx)
w = tvm.nd.array(np.random.uniform(-1, 1, wshape).astype(np.float32), ctx)
y = tvm.nd.array(np.random.uniform(-1, 1, yshape).astype(np.float32), ctx)
f(x, w, y)
Y_ref = topi.nn.conv2d_nchw(
X, W, (stride_h, stride_w), (pad_h, pad_w), (dilation_h, dilation_w)
)
s_ref = te.create_schedule(Y_ref.op)
f_ref = tvm.build(s_ref, [X, W, Y_ref], "rocm", target_host="llvm")
y_ref = tvm.nd.array(np.random.uniform(-1, 1, yshape).astype(np.float32), ctx)
f_ref(x, w, y_ref)
print("Max abs diff:", np.max(np.abs(y.asnumpy() - y_ref.asnumpy())))
tvm.testing.assert_allclose(y.asnumpy(), y_ref.asnumpy(), atol=1e-3)
verify()
if __name__ == "__main__":
test_conv2d()