[microNPU][2b] Create CascaderGraphs from TE graphs #9471
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jacobbohlin
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Jan 5, 2022
The first step in the cascader is to create a CascaderGraph from a TE graph. To do this, every operator in the TE graph must get 'matched' by a Part matcher. This converts TE operations into cascader Parts by augmenting them with Propagators. In this initial commit, we include basic Part matchers for ethosu_conv2d and some transform operators so that the graph creation can be tested. Change-Id: I36bbbdbafd14f09e6d1a8abf32591d6755192915
Change-Id: I34e48e4ce4fd14e6c92601412f5029aa08efe8fc
Change-Id: Idcb92c26863837b06fa68f9122a1a79df79ee242
Change-Id: I0aad319b7722a56b5c7f116adcc791951223baa3
Change-Id: Ib1633341ed84e83c29c4220dd9bc4a7b6d17a5d0
Change-Id: I5223da462a8dadfda1798e1ea1c9b30b4e804217
Change-Id: Ib614c21e97723571aa002a2a4a3edda3afafb9d4
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cc @Mousius could you take a look? |
Mousius
requested changes
Jan 7, 2022
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| write = output_tensor | ||
| if write.op.name != "ethosu_write": | ||
| return None | ||
| convert_to_nhcwb16 = write.op.input_tensors[0] | ||
| if convert_to_nhcwb16.op.name != "ethosu_convert_to_nhcwb16": | ||
| return None | ||
| conv2d = convert_to_nhcwb16.op.input_tensors[0] | ||
| if conv2d.op.name != "ethosu_conv2d": | ||
| return None | ||
| pad = conv2d.op.input_tensors[0] | ||
| if pad.op.name != "ethosu_pad": | ||
| return None | ||
| convert_to_nhwc = pad.op.input_tensors[0] | ||
| if convert_to_nhwc.op.name != "ethosu_convert_to_nhwc": | ||
| return None | ||
| read = convert_to_nhwc.op.input_tensors[0] | ||
| if read.op.name != "ethosu_read": | ||
| return None |
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I can't see test cases for all of these clauses, so we're missing most of the logic of this function? Can you add some?
| part = match_ethosu_conv2d(out) | ||
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| assert isinstance(part, cs.EthosuPart) | ||
| assert len(part.propagators) == 3 |
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Can we test the other properties of the part returned?
| part = match_ethosu_inline(out) | ||
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| assert isinstance(part, cs.InlinePart) | ||
| assert len(part.propagators) == 1 |
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Can we test the other properties of the part ?
| ) | ||
| pytest.importorskip("ethosu.vela") | ||
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| import tvm.contrib.ethosu.cascader as cs |
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As much as I appreciate using my initials here, it'd be really great to use something I could immediately associate with the cascader; potentially cascader rather than cs ?
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| assert part.propagators[0].transform == ifm_transform | ||
| assert part.propagators[0].offset == ifm_offset |
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It would be good to test at least a few cases just to ensure the function doesn't always return the same thing 😸
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| if output_tensor.op.name not in INLINE_OPS: | ||
| return None |
| input_tensors = part.subgraph.input_tensors | ||
| break | ||
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| assert part is not None, f"The tensor {tensor} doesn't match any part." |
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Would be good to ensure this fires when we expect it to with pytest.raises.
AndrewZhaoLuo
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Jan 7, 2022
The first step in the cascader is to create a CascaderGraph from a TE graph. To do this, every operator in the TE graph must get 'matched' by a Part matcher. This converts TE operations into cascader Parts by augmenting them with Propagators. In this initial commit, we include basic Part matchers for ethosu_conv2d and some transform operators so that the graph creation can be tested.
ylc
pushed a commit
to ylc/tvm
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this pull request
Feb 16, 2022
The first step in the cascader is to create a CascaderGraph from a TE graph. To do this, every operator in the TE graph must get 'matched' by a Part matcher. This converts TE operations into cascader Parts by augmenting them with Propagators. In this initial commit, we include basic Part matchers for ethosu_conv2d and some transform operators so that the graph creation can be tested.
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RFC: apache/tvm-rfcs#37
Issue: #9429
The first step in the cascader is to create a CascaderGraph from a TE graph. To do this, every operator in the TE graph must get 'matched' by a Part matcher. This converts TE operations into cascader Parts by augmenting them with Propagators.
In this initial commit, we include basic Part matchers for ethosu_conv2d and some transform operators so that the graph creation can be tested.