lhutton1 commented on code in PR #11453:
URL: https://github.com/apache/tvm/pull/11453#discussion_r885606921
##########
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:
Perhaps we should assert that `len(input_tensors_shape) <= 4` if we don't
support brick layout for identity
##########
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(),
Review Comment:
Seems a bit strange to need to use `.tolist()` for one of these and not the
other, is it possible that its not needed?
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