comaniac commented on a change in pull request #6999:
URL: https://github.com/apache/tvm/pull/6999#discussion_r532824650
##########
File path: tests/python/topi/python/test_topi_deformable_conv2d.py
##########
@@ -112,11 +115,94 @@ def check_device(device):
check_device(device)
+def verify_deformable_conv2d_nhwc(
+ batch,
+ in_channel,
+ in_size,
+ num_filter,
+ kernel,
+ stride,
+ padding,
+ dilation=1,
+ deformable_groups=1,
+ groups=1,
+):
+ print(
+ "Workload: (%d, %d, %d, %d, %d, %d, %d, %d, %d, %d)"
+ % (
+ batch,
+ in_channel,
+ in_size,
+ num_filter,
+ kernel,
+ stride,
+ padding,
+ dilation,
+ deformable_groups,
+ groups,
+ )
+ )
+
+ A = te.placeholder((batch, in_size, in_size, in_channel), name="A")
+ out_size = (in_size - (kernel - 1) * dilation - 1 + 2 * padding) // stride
+ 1
+ Offset = te.placeholder(
+ (batch, out_size, out_size, deformable_groups * kernel * kernel * 2),
name="offset"
+ )
+ W = te.placeholder((kernel, kernel, in_channel, num_filter), name="W")
+ bias = te.placeholder((num_filter,), name="bias")
+
+ a_shape = get_const_tuple(A.shape)
+ offset_shape = get_const_tuple(Offset.shape)
+ w_shape = get_const_tuple(W.shape)
+ bias_shape = get_const_tuple(bias.shape)
+ dtype = A.dtype
+
+
@memoize("topi.tests.test_topi_deformable_conv2d_nchw.verify_deformable_conv2d_nhwc")
+ def get_ref_data():
+ a_np = np.random.uniform(size=a_shape).astype(dtype)
+ offset_np = np.random.randn(*offset_shape).astype(dtype)
+ w_np = np.random.uniform(size=w_shape).astype(dtype)
+ b_np = np.random.uniform(size=bias_shape).astype(dtype)
+ c_np = tvm.topi.testing.deformable_conv2d_nhwc_python(
+ a_np, offset_np, w_np, stride, padding, dilation,
deformable_groups, groups
+ )
+
+ return a_np, offset_np, w_np, c_np
+
+ a_np, offset_np, w_np, c_np = get_ref_data()
+
+ def check_device(device):
+ ctx = tvm.context(device, 0)
+ if not tvm.testing.device_enabled(device):
+ print("Skip because %s is not enabled" % device)
+ return
+ print("Running on target: %s" % device)
+ fcompute, fschedule = tvm.topi.testing.dispatch(device,
_deformable_conv2d_nhwc_implement)
+ with tvm.target.Target(device):
+ C = fcompute(A, Offset, W, stride, padding, dilation,
deformable_groups, groups, dtype)
+ s = fschedule([C])
+
+ a = tvm.nd.array(a_np, ctx)
+ offset = tvm.nd.array(offset_np, ctx)
+ w = tvm.nd.array(w_np, ctx)
+ c = tvm.nd.empty(c_np.shape, dtype=c_np.dtype, ctx=ctx)
+
+ func = tvm.build(s, [A, Offset, W, C], device)
+ func(a, offset, w, c)
+ tvm.testing.assert_allclose(c.asnumpy(), c_np, rtol=1e-5)
+
+ for device in ["llvm"]:
Review comment:
Ah nvm. I forgot the default schedule doesn't work for GPU.
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