[GitHub] [tvm] lhutton1 commented on a diff in pull request #11453: [microNPU] Add transform matrices and part matcher to identity op

[GitBox <gi...@apache.org>]

lhutton1 commented on code in PR #11453:
URL: https://github.com/apache/tvm/pull/11453#discussion_r886898788


##########
python/tvm/relay/backend/contrib/ethosu/te/identity.py:
##########
@@ -76,7 +78,85 @@ def identity_compute(
         name="ethosu_identity",
         attrs=id_attrs,
     )
+    length = len(ifm.shape)
+    ifm_matrix = np.identity(length + 1)
+    offset = np.zeros(length, dtype="int64")
+    ifm_propagator = Propagator(
+        ifm_matrix,
+        offset.tolist(),
+    )
+    propagator_attrs = {
+        "ifm_propagator": ifm_propagator,
+    }
+    return write_compute(identity, ofm_zero_point, ofm_scale, attrs=propagator_attrs)
+
+
+@register_matcher
+def match_ethosu_identity(output_tensor, device_config):
+    """Match a Tensor Expression corresponding to an NPU identity.
 
-    dmaed_ofm = write_compute(identity, ofm_zero_point, ofm_scale)
+    If the Tensor Expression matches, an EthosuPart will be created that models the
+    matched Tensor Expression. Otherwise, None will be returned.
 
-    return dmaed_ofm
+    Parameters
+    ----------
+    output_tensor : tvm.te.Tensor
+        The tensor to attempt to match with.
+    device_config : EthosuDeviceConfig
+        Target device configuration
+
+    Returns
+    -------
+    Union[None, EthosuPart]
+        The created EthosuPart if there was a match, otherwise None.
+    """
+    write = output_tensor
+    if write.op.name != "ethosu_write":
+        return None
+    identity = write.op.input_tensors[0]
+    if identity.op.name != "ethosu_identity":
+        return None
+    read = identity.op.input_tensors[0]
+    if read.op.name != "ethosu_read":
+        return None
+
+    input_tensors = [
+        read.op.input_tensors[0],
+    ]
+    subgraph = TESubgraph(input_tensors, output_tensor)
+    propagators = [
+        write.op.attrs["ifm_propagator"],
+    ]
+    ifm_dtype = input_tensors[0].dtype
+    ofm_dtype = output_tensor.dtype
+
+    input_tensors_shape = input_tensors[0].shape
+    length = len(input_tensors_shape)
+    channels = int(input_tensors_shape[length - 1]) if length >= 3 else 1
+
+    subkernels = len(device_config.get_kernel_steps(identity.op.name, 1, 1, ifm_dtype))
+
+    input_layout = output_layout = "NHWC"

Review Comment:
   Ah, apologies, I should have said that a message would have been helpful alongside the assert as well. Lets take it in a follow up :)



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