"""Test code for bilinear scale """ import numpy as np import tvm import topi import topi.testing import math def verify_bilinear_scale(batch, in_channel, in_height, in_width, out_height, out_width, layout='NCHW', align_corners=False): if layout == 'NCHW': A = tvm.placeholder((batch, in_channel, in_height, in_width), name='A', dtype='float32') dtype = A.dtype out_shape = (batch, in_channel, out_height, out_width) a_np = np.random.uniform(size=(batch, in_channel, in_height, in_width)).astype(dtype) elif layout == 'NHWC': A = tvm.placeholder((batch, in_height, in_width, in_channel), name='A', dtype='float32') dtype = A.dtype out_shape = (batch, out_height, out_width, in_channel) a_np = np.random.uniform(size=(batch, in_height, in_width, in_channel)).astype(dtype) else: raise NotImplementedError( 'Layout not supported {} '.format(layout)) B = topi.image.resize(A, (out_height, out_width), layout=layout, align_corners=align_corners) b_np = topi.testing.bilinear_resize_python(a_np, (out_height, out_width), layout, align_corners) 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) np.testing.assert_allclose(b.asnumpy(), b_np, rtol=1e-3, atol=1e-3) for device in ['llvm', 'cuda', 'vulkan', 'nvptx']: check_device(device) def test_resize(): # Scale NCHW verify_bilinear_scale(4, 16, 32, 32, 50, 50, 'NCHW') # Scale NCHW + Align Corners verify_bilinear_scale(6, 32, 64, 64, 20, 20, 'NCHW', True) # Scale NHWC verify_bilinear_scale(4, 16, 32, 32, 50, 50, "NHWC") # Scale NHWC + Align Corners verify_bilinear_scale(6, 32, 64, 64, 20, 20, "NHWC", True) if __name__ == "__main__": test_resize()