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11 | 11 | from numba.core.caching import CacheImpl, _CacheLocator
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12 | 12 |
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13 | 13 | from pytensor import config
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14 |
| -from pytensor.graph.basic import Apply |
15 | 14 | from pytensor.link.numba.compile import numba_funcify, numba_njit
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16 | 15 |
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17 | 16 |
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@@ -65,22 +64,6 @@ def from_function(cls, py_func, py_file):
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65 | 64 | CacheImpl._locator_classes.insert(0, NumbaPyTensorCacheLocator)
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66 | 65 |
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67 | 66 |
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68 |
| -def cache_node_key(node: Apply, extra_key="") -> str: |
69 |
| - op = node.op |
70 |
| - return sha256( |
71 |
| - str( |
72 |
| - ( |
73 |
| - # Op signature |
74 |
| - (type(op), op._props_dict() if hasattr(op, "_props_dict") else ""), |
75 |
| - # Node signature |
76 |
| - tuple((type(inp_type := inp.type), inp_type) for inp in node.inputs), |
77 |
| - # Extra key given by the caller |
78 |
| - extra_key, |
79 |
| - ), |
80 |
| - ).encode() |
81 |
| - ).hexdigest() |
82 |
| - |
83 |
| - |
84 | 67 | @singledispatch
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85 | 68 | def numba_funcify_default_op_cache_key(
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86 | 69 | op, node=None, **kwargs
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@@ -109,7 +92,7 @@ def decorator(dispatch_func):
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109 | 92 | # Create a wrapper for the non-cache dispatcher
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110 | 93 | @wraps(dispatch_func)
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111 | 94 | def dispatch_func_wrapper(*args, **kwargs):
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112 |
| - func, key = dispatch_func(*args, **kwargs) |
| 95 | + func, _key = dispatch_func(*args, **kwargs) |
113 | 96 | # Discard the key for the non-cache version
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114 | 97 | return func
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115 | 98 |
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@@ -172,7 +155,7 @@ def decorator(dispatch_func):
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172 | 155 | # Create a wrapper for the non-cache dispatcher
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173 | 156 | @wraps(dispatch_func)
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174 | 157 | def dispatch_func_wrapper(*args, **kwargs):
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175 |
| - func, key = dispatch_func(*args, **kwargs) |
| 158 | + func, _key = dispatch_func(*args, **kwargs) |
176 | 159 | # Discard the key for the non-cache version
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177 | 160 | return func
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178 | 161 |
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