srkreddy1238 commented on code in PR #13834:
URL: https://github.com/apache/tvm/pull/13834#discussion_r1086232498
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tests/python/contrib/test_clml/test_ops.py:
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@@ -574,5 +574,107 @@ def _verify(out, params, inputs):
_verify(*(_get_model((1, 16), relay.nn.relu)))
[email protected]("dtype", ["float32"])
[email protected]_openclml
+def test_depth_to_space(device, dtype):
+ def _get_model(a_shape, block_size):
+ a = relay.var("a", shape=(a_shape), dtype=dtype)
+ out = relay.nn.depth_to_space(a, block_size)
+ inputs = {"a": tvm.nd.array(np.random.uniform(-1, 1,
a_shape).astype(dtype))}
+ params = {}
+ return out, params, inputs
+
+ def _verify(out, params, inputs):
+ mod = IRModule.from_expr(out)
+ opencl_out = build_and_run(mod, inputs, 1, params, device,
enable_clml=False)[0]
+ clml_out = build_and_run(mod, inputs, 1, params, device,
enable_clml=True)[0]
+ tvm.testing.assert_allclose(
+ clml_out[0].asnumpy(), opencl_out[0].asnumpy(), rtol=1e-3,
atol=1e-3
+ )
+
+ # Check to make sure these ops are offloaded to CLML instead of TVM.
+ exp_codegen = [
+ {
+ "attrs": {
+ "dtype": [[dtype]],
+ "shape": [[list(inputs["a"].shape)]],
+ },
+ "name": "",
+ "op": "input",
+ },
+ {
+ "attrs": {
+ "block_size": [[str(int(out.attrs.block_size))]],
+ "layout": [["NCHW"]],
+ "mode": [["DCR"]],
+ "dtype": [[dtype]],
+ "num_inputs": "1",
+ "num_outputs": "1",
+ "shape": [[list(clml_out[0].shape)]],
+ },
+ "inputs": [[0, 0, 0]],
+ "name": "nn.depth_to_space",
+ "op": "kernel",
+ },
+ ]
+ verify_codegen(out, exp_codegen, device, params)
+
+ _verify(*(_get_model((1, 64, 8, 8), 4)))
+ _verify(*(_get_model((1, 64, 8, 8), 8)))
+
+
[email protected]("dtype", ["float32"])
Review Comment:
Can we cover "float16" also here if supported on CLML & TVM too ?
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