Fix bops calculation #1369
Fix bops calculation #1369
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@irenaby |
| reuse=weights_node.reuse, | ||
| reuse_group=weights_node.reuse_group, | ||
| quantization_attr=weights_node.quantization_attr, | ||
| has_activation=False) | ||
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| self.name = f"{VIRTUAL_ACTIVATION_WEIGHTS_NODE_PREFIX}_{act_node.name}_{weights_node.name}" |
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isn't this a duplicate? of line 152?
# Conflicts: # tests_pytest/common_tests/unit_tests/core/mixed_precision/resource_utilization_tools/test_resource_utilization_calculator.py # tests_pytest/pytorch_tests/torch_test_util/torch_test_mixin.py
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| self.original_activation_node = act_node | ||
| self.original_weights_node = weights_node | ||
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| v_candidates = [] | ||
| kernel_attr = fw_info.get_kernel_op_attributes(weights_node.type)[0] |
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Why restrict only to kernel attr? In theory all attr may have candidates.
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Not supported, added check that no other atrrs are configurable.
| # we don't need the original node (and cannot use it for custom configuration anyway) | ||
| a_node = n | ||
| else: | ||
| a_node = get_input_activation_if_composable(self.graph, n, warn=False) |
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In what case will we get here? shouldn't activation nodes followed by kernel nodes be already fused into VirtualActivationWeightsNode
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In case we run on the original graph, added comment.
| outputs = Dense(10)(x) | ||
| return keras.Model(inputs=inputs, outputs=outputs) | ||
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| def _build_mult_output_activation_model(self): |
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its input activation with mult output
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| return Model() | ||
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| def _build_mult_output_activation_model(self): |
Pull Request Description:
Support for bops computation on virtual nodes in RU calculator.
Updated virtual graph substitutions to fix activation & weights RU calculation on virtual graph.
Use RU calculator for bops in mixed precision search.
Added integration tests for RU calculator (framework -> graph preparation -> RU calculator, original vs virtual graph).
Added verification that target RU is satisfied by final RU in MP tests.
Checklist before requesting a review: