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⚡ Bolt: Refactor AlgebraicSimplifyPass for Performance #6

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⚡ Bolt: Refactor AlgebraicSimplifyPass for Performance #6

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8 changes: 7 additions & 1 deletion tests/test_consistency.py
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Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,13 @@
from graph_optimizer.core import GraphOptimizer, OptimizationContext
from graph_optimizer.utils import create_node, make_output_shapes_attr, create_const_node
from graph_optimizer.transforms.vectorize import PackVectorizePass
from graph_optimizer.transforms.scalar import AlgebraicSimplifyPass, ConstantFoldPass
from graph_optimizer.transforms.scalar import (
ConstantFoldPass,
SimplifyAddPass,
SimplifySubPass,
SimplifyMulPass,
SimplifyDivPass,
)
from tensorflow.core.framework import attr_value_pb2
from graph_optimizer.utils.logger import set_log_level
import logging
Expand Down
14 changes: 6 additions & 8 deletions tests/test_edge_cases.py
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Original file line number Diff line number Diff line change
@@ -1,9 +1,8 @@
import tensorflow.compat.v1 as tf
import numpy as np
from graph_optimizer.core import GraphOptimizer
from graph_optimizer.transforms.scalar.algebraic_simplify import AlgebraicSimplifyPass
from graph_optimizer.core import GraphOptimizer, PassRegistry
from graph_optimizer.utils.graph_utils import create_node, create_const_node

from graph_optimizer.transforms.scalar.constant_fold import ConstantFoldPass

def test_shape_breakage():
# Construct a graph:
Expand All @@ -27,7 +26,7 @@ def test_shape_breakage():
graph_def.node.extend([x, eq, sink])

optimizer = GraphOptimizer(graph_def)
pass_instance = AlgebraicSimplifyPass()
pass_instance = PassRegistry.get_pass("simplify_redundant_comparison")

print("Before optimization:")
print(f"eq_node: {optimizer.nodes['eq_node'].op}")
Expand All @@ -36,8 +35,8 @@ def test_shape_breakage():
pass_instance.transform(optimizer, protected_nodes=["sink"])

print("\nAfter optimization:")
if "eq_node_bool" in optimizer.nodes:
new_node = optimizer.nodes["eq_node_bool"]
if "eq_node" in optimizer.nodes and optimizer.nodes["eq_node"].op == "Const":
new_node = optimizer.nodes["eq_node"]
print(f"Replacement node op: {new_node.op}")

# Check shape in top-level or in tensor
Expand Down Expand Up @@ -68,7 +67,6 @@ def test_div_zero():
graph_def.node.extend([c1, c0, div])

optimizer = GraphOptimizer(graph_def)
from graph_optimizer.transforms.scalar.constant_fold import ConstantFoldPass

pass_instance = ConstantFoldPass()

Expand Down Expand Up @@ -97,7 +95,7 @@ def test_broadcasting_safety():
graph_def.node.extend([x, zero, add, sink])

optimizer = GraphOptimizer(graph_def)
pass_instance = AlgebraicSimplifyPass()
pass_instance = PassRegistry.get_pass("simplify_add")

print("\n--- Broadcasting Safety Test ---")
pass_instance.transform(optimizer, protected_nodes=["sink"])
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