Move exceptions defined in theano.tensor to theano.tensor.exceptions

doc/extending/fibby.txt

@@ -108,7 +108,8 @@ TODO: talk about OPTIMIZATION STAGES
 
 .. testcode::
 
-   from theano.tensor.opt import get_scalar_constant_value, NotScalarConstantError
+   from theano.tensor.basic import get_scalar_constant_value
+   from theano.tensor.exceptions import NotScalarConstantError
 
    # Remove any fibby(zeros(...))
    @theano.tensor.opt.register_specialize

setup.cfg

@@ -47,4 +47,4 @@ lines_after_imports = 2
 lines_between_sections = 1
 honor_noqa = True
 skip_gitignore = True
-skip = theano/version.py
+skip = theano/version.py, **/__init__.py
\ No newline at end of file

tests/tensor/nnet/test_conv.py

@@ -7,7 +7,8 @@ import theano
 import theano.tensor as tt
 from tests import unittest_tools as utt
 from theano.compile.mode import Mode
-from theano.tensor.basic import NotScalarConstantError, _allclose
+from theano.tensor.basic import _allclose
+from theano.tensor.exceptions import NotScalarConstantError
 from theano.tensor.nnet import conv, conv2d
 from theano.tensor.type import dmatrix, dtensor3, dtensor4, dvector, scalar, tensor4
 

theano/__init__.py

@@ -112,13 +112,13 @@ if (
 def get_scalar_constant_value(v):
     """Return the constant scalar (i.e. 0-D) value underlying variable `v`.
 
-    If v is the output of dimshuffles, fills, allocs, rebroadcasts, cast
+    If `v` is the output of dim-shuffles, fills, allocs, rebroadcasts, cast
     this function digs through them.
 
-    If theano.sparse is also there, we will look over CSM op.
+    If ``theano.sparse`` is also there, we will look over CSM `Op`.
 
     If `v` is not some view of constant data, then raise a
-    tensor.basic.NotScalarConstantError.
+    `NotScalarConstantError`.
     """
     # Is it necessary to test for presence of theano.sparse at runtime?
     sparse = globals().get("sparse")

theano/compile/ops.py

@@ -894,7 +894,7 @@ class SpecifyShape(COp):
                 s = theano.tensor.get_scalar_constant_value(node.inputs[1][dim])
                 s = theano.tensor.as_tensor_variable(s)
                 new_shape.append(s)
-            except theano.tensor.basic.NotScalarConstantError:
+            except theano.tensor.exceptions.NotScalarConstantError:
                 new_shape.append(node.inputs[1][dim])
 
         assert len(new_shape) == len(xshape)

theano/gpuarray/dnn.py

@@ -37,7 +37,8 @@ from theano.scalar import bool as bool_t
 from theano.scalar import constant, get_scalar_type
 from theano.scalar import int32 as int_t
 from theano.scalar import uint32 as uint32_t
-from theano.tensor.basic import NotScalarConstantError, as_tensor_variable
+from theano.tensor.basic import as_tensor_variable
+from theano.tensor.exceptions import NotScalarConstantError
 from theano.tensor.extra_ops import cpu_contiguous
 from theano.tensor.nnet.abstract_conv import (
     AbstractConv2d,

theano/gpuarray/multinomial.py

@@ -24,7 +24,8 @@ from theano.gpuarray.type import GpuArrayType
 from theano.graph.basic import Apply
 from theano.graph.op import _NoPythonOp
 from theano.scalar import as_scalar
-from theano.tensor.basic import NotScalarConstantError, get_scalar_constant_value
+from theano.tensor.basic import get_scalar_constant_value
+from theano.tensor.exceptions import NotScalarConstantError
 
 
 class GPUAMultinomialFromUniform(GpuKernelBaseCOp, _NoPythonOp):

theano/gpuarray/opt_util.py

@@ -16,8 +16,9 @@ from theano.gpuarray.type import GpuArrayType, get_context, move_to_gpu
 from theano.graph.basic import Constant
 from theano.graph.op import Op
 from theano.graph.opt import copy_stack_trace, inherit_stack_trace, local_optimizer
-from theano.tensor.basic import NotScalarConstantError, get_scalar_constant_value
+from theano.tensor.basic import get_scalar_constant_value
 from theano.tensor.elemwise import DimShuffle
+from theano.tensor.exceptions import NotScalarConstantError
 from theano.tensor.type import TensorType
 
 

theano/gradient.py

@@ -2114,7 +2114,7 @@ def _is_zero(x):
     try:
         constant_value = theano.get_scalar_constant_value(x)
         no_constant_value = False
-    except theano.tensor.basic.NotScalarConstantError:
+    except theano.tensor.exceptions.NotScalarConstantError:
         pass
 
     if no_constant_value:

theano/sandbox/linalg/ops.py

@@ -8,6 +8,7 @@ from theano.tensor import basic as tt
 from theano.tensor.basic import Dot
 from theano.tensor.blas import Dot22
 from theano.tensor.elemwise import DimShuffle, Prod
+from theano.tensor.exceptions import NotScalarConstantError
 from theano.tensor.nlinalg import (
     MatrixInverse,
     det,
@@ -210,7 +211,7 @@ def is_positive(v):
     if v.owner and v.owner.op == tt.pow:
         try:
             exponent = tt.get_scalar_constant_value(v.owner.inputs[1])
-        except tt.NotScalarConstantError:
+        except NotScalarConstantError:
             return False
         if 0 == exponent % 2:
             return True

theano/scan/basic.py

@@ -27,7 +27,7 @@ from theano.scan import utils
 from theano.scan.op import Scan
 from theano.scan.utils import safe_new, traverse
 from theano.tensor import opt
-from theano.tensor.basic import NotScalarConstantError
+from theano.tensor.exceptions import NotScalarConstantError
 from theano.tensor.type import TensorType, integer_dtypes
 from theano.updates import OrderedUpdates
 

theano/tensor/__init__.py

@@ -5,6 +5,7 @@ __docformat__ = "restructuredtext en"
 
 import warnings
 
+import theano.tensor.exceptions
 from theano.compile.ops import shape, specify_shape
 from theano.gradient import consider_constant, grad, hessian, jacobian
 from theano.tensor import sharedvar  # adds shared-variable constructors

theano/tensor/basic.py

@@ -23,6 +23,7 @@ from theano.printing import min_informative_str, pprint
 from theano.scalar import int32
 from theano.tensor import elemwise
 from theano.tensor.elemwise import CAReduce, DimShuffle, Elemwise, Sum, scalar_elemwise
+from theano.tensor.exceptions import EmptyConstantError, NotScalarConstantError
 from theano.tensor.type import (
     TensorType,
     complex_dtypes,
@@ -46,10 +47,6 @@ _logger = logging.getLogger("theano.tensor.basic")
 __docformat__ = "restructuredtext en"
 
 
-class ShapeError(Exception):
-    """Raised when the shape cannot be computed."""
-
-
 def check_equal_numpy(x, y):
     """
     Return True iff x and y are equal.
@@ -333,20 +330,6 @@ def _allclose(a, b, rtol=None, atol=None):
     return np.allclose(a, b, atol=atol_, rtol=rtol_)
 
 
-class NotScalarConstantError(Exception):
-    """
-    Raised by get_scalar_constant_value if called on something that is
-    not a scalar constant.
-    """
-
-
-class EmptyConstantError(NotScalarConstantError):
-    """
-    Raised by get_scalar_const_value if called on something that is a
-    zero dimensional constant.
-    """
-
-
 def numpy_scalar(data):
     """Return a scalar stored in a numpy ndarray.
 
@@ -1867,7 +1850,7 @@ def round(a, mode=None):
     elif mode == "half_to_even":
         return round_half_to_even(a)
     else:
-        raise Exception(f"round mode {mode} is not implemented.")
+        raise NotImplementedError(f"round mode {mode} is not implemented.")
 
 
 @scalar_elemwise

theano/tensor/blas.py

@@ -162,6 +162,7 @@ from theano.scalar import bool as bool_t
 from theano.tensor import basic as tt
 from theano.tensor.blas_headers import blas_header_text, blas_header_version
 from theano.tensor.elemwise import DimShuffle, Elemwise
+from theano.tensor.exceptions import NotScalarConstantError
 from theano.tensor.opt import in2out, local_dimshuffle_lift
 from theano.tensor.type import integer_dtypes, values_eq_approx_remove_inf_nan
 from theano.utils import memoize
@@ -1729,7 +1730,7 @@ def local_gemm_to_ger(fgraph, node):
                 yv = y.dimshuffle(1)
                 try:
                     bval = tt.get_scalar_constant_value(b)
-                except tt.NotScalarConstantError:
+                except NotScalarConstantError:
                     # b isn't a constant, GEMM is doing useful pre-scaling
                     return
 

theano/tensor/exceptions.py

+class ShapeError(Exception):
+    """Raised when the shape cannot be computed."""
+
+
+class NotScalarConstantError(Exception):
+    """
+    Raised by get_scalar_constant_value if called on something that is
+    not a scalar constant.
+    """
+
+
+class EmptyConstantError(NotScalarConstantError):
+    """
+    Raised by get_scalar_const_value if called on something that is a
+    zero dimensional constant.
+    """
+
+
+class AdvancedIndexingError(TypeError):
+    """
+    Raised when Subtensor is asked to perform advanced indexing.
+
+    """

theano/tensor/extra_ops.py

@@ -19,6 +19,7 @@ from theano.scalar import int32 as int_t
 from theano.scalar import upcast
 from theano.tensor import basic as tt
 from theano.tensor import nlinalg
+from theano.tensor.exceptions import NotScalarConstantError
 from theano.tensor.subtensor import advanced_inc_subtensor1, set_subtensor
 from theano.tensor.type import (
     TensorType,
@@ -690,7 +691,7 @@ class RepeatOp(Op):
         else:
             try:
                 const_reps = tt.get_scalar_constant_value(repeats)
-            except tt.NotScalarConstantError:
+            except NotScalarConstantError:
                 const_reps = None
             if const_reps == 1:
                 broadcastable = x.broadcastable

theano/tensor/nnet/conv.py

@@ -483,7 +483,7 @@ class ConvOp(OpenMPOp):
 
         all_shape = self.has_all_shape(imshp, kshp, nkern, bsize)
         if (unroll_batch or unroll_kern) and not all_shape:
-            raise Exception(
+            raise ValueError(
                 "In ConvOp, when using unroll_batch and"
                 " unroll_nkern, all shape are needed"
             )
@@ -613,10 +613,10 @@ class ConvOp(OpenMPOp):
         self.out_mode = output_mode
 
         if self.out_mode not in ["valid", "full"]:
-            raise Exception(f"Mode {self.out_mode} not implemented")
+            raise NotImplementedError(f"Mode {self.out_mode} not implemented")
 
         if any((shp is not None) and (shp <= 0) for shp in self.outshp):
-            raise Exception(
+            raise ValueError(
                 "Bad size for the output shape. Verify that [post-"
                 f"supersampling] input shape ({self.imshp_logical}) and kern"
                 f" shape({self.kshp_logical}) are ok. (Hint: kerns must fit inside"
@@ -1038,7 +1038,7 @@ class ConvOp(OpenMPOp):
         all_shape = self.has_all_shape(self.imshp, self.kshp, self.nkern, self.bsize)
 
         if not all_shape and (self.dx != 1 or self.dy != 1):
-            raise Exception(
+            raise ValueError(
                 "ConvOp.grad when dx!=1 or dy!=1 we must have all "
                 "the optional shape information"
             )
@@ -1486,7 +1486,9 @@ if(kerns_dim[1] != img2d_dim[1]){
         elif node.inputs[0].type.dtype == "float64":
             d["type"] = "double"
         else:
-            raise Exception(f"Type {node.inputs[0].type.dtype} not implemented")
+            raise NotImplementedError(
+                f"Type {node.inputs[0].type.dtype} not implemented"
+            )
         d["gemm"] = "dgemm_"
         if not d["type"] == "double":
             d["gemm"] = "sgemm_"
@@ -2042,8 +2044,8 @@ def gen_conv_code_unroll_batch_kern(d, unroll_bsize=1, unroll_ksize=1):
         or "unroll_biter" in d
         or "unroll_kiter" in d
     ):
-        raise Exception(
-            "We can't use this dictionary as we will overwrite some of its containt"
+        raise ValueError(
+            "We can't use this dictionary as we will overwrite some of its content"
         )
     d = d.copy()
 

theano/tensor/nnet/nnet.py

@@ -34,6 +34,7 @@ from theano.tensor import basic as tt
 from theano.tensor import extra_ops, opt
 from theano.tensor.basic import MaxAndArgmax, as_tensor_variable, log
 from theano.tensor.elemwise import Elemwise
+from theano.tensor.exceptions import NotScalarConstantError
 from theano.tensor.nnet.blocksparse import sparse_block_dot
 from theano.tensor.nnet.sigm import sigmoid, softplus
 from theano.tensor.opt import (
@@ -1758,7 +1759,7 @@ def _check_rows_is_arange_len_labels(fgraph, rows, labels):
 def _is_const(z, val, approx=False):
     try:
         maybe = opt.get_scalar_constant_value(z)
-    except tt.NotScalarConstantError:
+    except NotScalarConstantError:
         return False
     if approx:
         return np.allclose(maybe, val)

theano/tensor/nnet/sigm.py

@@ -20,8 +20,8 @@ from theano.graph.utils import MethodNotDefined
 from theano.printing import pprint
 from theano.tensor import basic as tt
 from theano.tensor import opt
-from theano.tensor.basic import NotScalarConstantError
 from theano.tensor.elemwise import Elemwise
+from theano.tensor.exceptions import NotScalarConstantError
 from theano.tensor.type import TensorType, values_eq_approx_remove_inf
 
 
@@ -463,7 +463,7 @@ def _is_1(expr):
     try:
         v = opt.get_scalar_constant_value(expr)
         return np.allclose(v, 1)
-    except tt.NotScalarConstantError:
+    except NotScalarConstantError:
         return False
 
 
@@ -1074,7 +1074,7 @@ def local_1msigmoid(fgraph, node):
         if sub_r.owner and sub_r.owner.op == sigmoid:
             try:
                 val_l = opt.get_scalar_constant_value(sub_l)
-            except tt.NotScalarConstantError:
+            except NotScalarConstantError:
                 return
             if np.allclose(np.sum(val_l), 1):
                 out = sigmoid(-sub_r.owner.inputs[0])

theano/tensor/opt.py

@@ -62,11 +62,9 @@ from theano.tensor.basic import (
     Dot,
     Flatten,
     Join,
-    NotScalarConstantError,
     Rebroadcast,
     Reshape,
     ScalarFromTensor,
-    ShapeError,
     Split,
     TensorFromScalar,
     Tile,
@@ -99,6 +97,7 @@ from theano.tensor.elemwise import (
     ProdWithoutZeros,
     Sum,
 )
+from theano.tensor.exceptions import NotScalarConstantError, ShapeError
 from theano.tensor.extra_ops import broadcast_shape
 from theano.tensor.sort import TopKOp
 from theano.tensor.subtensor import (
@@ -1115,7 +1114,7 @@ class ShapeFeature(toolbox.Feature):
                 "Code called by infer_shape failed raising a "
                 "NotImplementedError. Raising NotImplementedError to "
                 "indicate that a shape cannot be computed is no longer "
-                "supported, and one should now use tensor.ShapeError "
+                "supported, and one should now use ShapeError "
                 f"instead. The original exception message is: {e}"
             ).with_traceback(e.__traceback__)
         except Exception as e:

theano/tensor/subtensor.py

@@ -26,6 +26,7 @@ from theano.tensor.basic import (
     get_scalar_constant_value,
 )
 from theano.tensor.elemwise import DimShuffle
+from theano.tensor.exceptions import AdvancedIndexingError, ShapeError
 from theano.tensor.inc_code import inc_code
 from theano.tensor.type import (
     bscalar,
@@ -62,13 +63,6 @@ invalid_tensor_types = (
 )
 
 
-class AdvancedIndexingError(TypeError):
-    """
-    Raised when Subtensor is asked to perform advanced indexing.
-
-    """
-
-
 def as_index_constant(a):
     """Convert Python literals to Theano constants--when possible--in Subtensor arguments.
 
@@ -2344,7 +2338,7 @@ class AdvancedSubtensor(Op):
                 isinstance(idx, (np.bool_, bool))
                 or getattr(idx, "dtype", None) == "bool"
             ):
-                raise theano.tensor.basic.ShapeError(
+                raise ShapeError(
                     "Shape inference for boolean indices is not implemented"
                 )
             # The `ishapes` entries for `SliceType`s will be None, and

theano/tensor/var.py

@@ -9,6 +9,7 @@ import theano
 from theano.configdefaults import config
 from theano.graph.basic import Constant, Variable
 from theano.scalar import ComplexError, IntegerDivisionError
+from theano.tensor.exceptions import AdvancedIndexingError
 from theano.tensor.type import TensorType
 from theano.tensor.utils import hash_from_ndarray
 
@@ -533,7 +534,7 @@ class _tensor_py_operators:
             if arg is not np.newaxis:
                 try:
                     theano.tensor.subtensor.Subtensor.convert(arg)
-                except theano.tensor.subtensor.AdvancedIndexingError:
+                except AdvancedIndexingError:
                     if advanced:
                         axis = None
                         break