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Reapply pyre-ignores after lintrunner moves
lintrunner moved the pyre-ignores to the wrong line, re-apply to the right line again. Signed-off-by: Per Åstrand <[email protected]> Change-Id: Icbb6cf6f2d65d6fe1c00e7c4a738691ffeb7acb2
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4 files changed

+8
-6
lines changed

4 files changed

+8
-6
lines changed

backends/arm/operators/op_conv2d.py

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@@ -8,6 +8,8 @@
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import serializer.tosa_serializer as ts
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import torch
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# pyre-fixme[21]: 'Could not find a module corresponding to import `executorch.backends.arm._passes.fold_qdq_with_annotated_qparams_pass`.'
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from executorch.backends.arm._passes.fold_qdq_with_annotated_qparams_pass import (
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get_input_qparams,
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get_output_qparams,

backends/arm/operators/op_max.py

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@@ -45,9 +45,9 @@ def define_node(
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scale_back = 1.0
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max_output = output
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if inputs[0].dtype == ts.DType.INT8:
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input_qparams = get_input_qparams(
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input_qparams = get_input_qparams( # pyre-ignore[16]: 'Module `executorch.backends.arm` has no attribute `_passes`.'
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node
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) # pyre-ignore[16]: 'Module `executorch.backends.arm` has no attribute `_passes`.'
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)
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assert (
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len(input_qparams) == 2
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), f"Both inputs needs to have quantization information for {node}"

backends/arm/operators/op_min.py

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@@ -46,9 +46,9 @@ def define_node(
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scale_back = 1.0
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min_output = output
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if inputs[0].dtype == ts.DType.INT8:
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input_qparams = get_input_qparams(
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input_qparams = get_input_qparams( # pyre-ignore[16]: 'Module `executorch.backends.arm` has no attribute `_passes`.'
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node
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) # pyre-ignore[16]: 'Module `executorch.backends.arm` has no attribute `_passes`.'
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)
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assert (
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len(input_qparams) == 2
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), f"Both inputs needs to have quantization information for {node}"

backends/arm/process_node.py

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@@ -114,9 +114,9 @@ def process_quantized_bias(
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_,
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) = consumer_node.all_input_nodes
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input_qargs = get_input_qparams(
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input_qargs = get_input_qparams( # pyre-ignore[16]: Module `executorch.backends.arm` has no attribute `_passes`.
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consumer_node
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) # pyre-ignore[16]: Module `executorch.backends.arm` has no attribute `_passes`.
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)
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input_node_scale = input_qargs[0].scale
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weight_node_scale = input_qargs[1].scale

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