masahi commented on a change in pull request #4584: [TOPI] add 3D upsampling Op.
URL: https://github.com/apache/incubator-tvm/pull/4584#discussion_r361419440
##########
File path: topi/tests/python/test_topi_upsampling.py
##########
@@ -86,5 +86,71 @@ def test_upsampling():
verify_upsampling(2, 2, 32, 32, 3.0, 3.0, layout="NHWC", method="bilinear")
verify_upsampling(1, 64, 22, 32, 3.0, 3.0, layout="NHWC",
method="bilinear")
+def verify_upsampling3d(batch, in_channel, in_depth, in_height, in_width,
scale_d, scale_h, scale_w,
+ layout='NCDHW', method="nearest_neighbor"):
+ if layout == 'NCDHW':
+ A = tvm.placeholder((batch, in_channel, in_depth, in_height,
in_width), name='A')
+ dtype = A.dtype
+ out_shape = (batch, in_channel, int(round(in_depth*scale_d)),
int(round(in_height*scale_h)),
+ int(round(in_width*scale_w)))
+ a_np = np.random.uniform(size=(batch, in_channel, in_depth, in_height,
in_width)).astype(dtype)
+ elif layout == 'NDHWC':
+ A = tvm.placeholder((batch, in_depth, in_height, in_width,
in_channel), name='A')
+ dtype = A.dtype
+ out_shape = (batch, int(round(in_depth*scale_d)),
int(round(in_height*scale_h)),
+ int(round(in_width*scale_w)), in_channel)
+ a_np = np.random.uniform(size=(batch, in_depth, in_height, in_width,
in_channel)).astype(dtype)
+ else:
+ raise NotImplementedError(
+ 'Layout not supported {} '.format(layout))
+
+ B = topi.nn.upsampling3d(A, scale_d, scale_h, scale_w, layout=layout,
method=method, align_corners=False)
+
+ if method == "trilinear":
+ out_size = (int(round(in_depth*scale_d)),
int(round(in_height*scale_h)), int(round(in_width*scale_w)))
+ b_np = topi.testing.trilinear_resize3d_python(a_np, out_size, layout,
align_corners=False)
+ else:
+ b_np = topi.testing.upsampling3d_python(a_np, (scale_d, scale_h,
scale_w), layout)
+
+ def check_device(device):
+ ctx = tvm.context(device, 0)
+ if not ctx.exist:
+ print("Skip because %s is not enabled" % device)
+ return
+ print("Running on target: %s" % device)
+ with tvm.target.create(device):
+ s = topi.generic.schedule_injective(B)
+ a = tvm.nd.array(a_np, ctx)
+ b = tvm.nd.array(np.zeros(out_shape, dtype=dtype), ctx)
+ f = tvm.build(s, [A, B], device)
+ f(a, b)
+
+ tvm.testing.assert_allclose(b.asnumpy(), b_np, rtol=1e-5, atol=1e-5)
+
+ for device in get_all_backend():
+ check_device(device)
+
+def test_upsampling3d():
+ # nearest_neighbor - NCDHW
+ verify_upsampling3d(8, 8, 16, 16, 16, 2.0, 2.0, 2.0)
+ verify_upsampling3d(2, 16, 32, 32, 32, 3.0, 3.0, 3.0)
+ verify_upsampling3d(1, 8, 11, 16, 6, 1.954545497894287, 2.0, 1.5)
+
+ ## nearest_neighbor - NDHWC
+ verify_upsampling3d(8, 8, 16, 16, 16, 2.0, 2.0, 2.0, layout="NDHWC")
+ verify_upsampling3d(2, 16, 32, 32, 32, 3.0, 3.0, 3.0, layout="NDHWC")
+ verify_upsampling3d(1, 8, 11, 16, 6, 1.954545497894287, 2.0, 1.5,
layout="NDHWC")
+
+ # trilinear - NCDHW
+ verify_upsampling3d(2, 2, 16, 16, 16, 2.0, 2.0, 2.0, method="trilinear")
+ verify_upsampling3d(2, 2, 32, 32, 32, 3.0, 3.0, 3.0, method="trilinear")
+ verify_upsampling3d(1, 2, 11, 16, 6, 1.954545497894287, 2.0, 1.5,
method="trilinear")
+
+ # trilinear - NHWC
Review comment:
NDHWC
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