Apply isort to theano.tensor.nnet sub-package modules

theano/tensor/nnet/__init__.py

+import warnings
+
+from . import opt
+from .abstract_conv import conv2d as abstract_conv2d
+from .abstract_conv import conv2d_grad_wrt_inputs, conv3d, separable_conv2d
+from .bn import batch_normalization
+from .conv import ConvOp
 from .nnet import (
     CrossentropyCategorical1Hot,
     CrossentropyCategorical1HotGrad,
@@ -10,8 +17,8 @@ from .nnet import (
     SoftmaxGrad,
     SoftmaxWithBias,
     binary_crossentropy,
-    sigmoid_binary_crossentropy,
     categorical_crossentropy,
+    confusion_matrix,
     crossentropy_categorical_1hot,
     crossentropy_categorical_1hot_grad,
     crossentropy_softmax_1hot,
@@ -22,6 +29,7 @@ from .nnet import (
     crossentropy_softmax_max_and_argmax_1hot_with_bias,
     crossentropy_to_crossentropy_with_softmax,
     crossentropy_to_crossentropy_with_softmax_with_bias,
+    elu,
     graph_merge_softmax_with_crossentropy_softmax,
     h_softmax,
     logsoftmax,
@@ -30,35 +38,24 @@ from .nnet import (
     prepend_1_to_each_row,
     prepend_scalar_to_each_row,
     relu,
+    selu,
+    sigmoid_binary_crossentropy,
     softmax,
     softmax_grad,
     softmax_graph,
     softmax_op,
     softmax_simplifier,
     softmax_with_bias,
-    elu,
-    selu,
-    confusion_matrix,
     softsign,
 )
-from . import opt
-from .conv import ConvOp
 from .sigm import (
-    softplus,
+    hard_sigmoid,
+    scalar_sigmoid,
     sigmoid,
     sigmoid_inplace,
-    scalar_sigmoid,
+    softplus,
     ultra_fast_sigmoid,
-    hard_sigmoid,
 )
-from .bn import batch_normalization
-
-
-import warnings
-from .abstract_conv import conv2d as abstract_conv2d
-from .abstract_conv import conv2d_grad_wrt_inputs
-from .abstract_conv import conv3d
-from .abstract_conv import separable_conv2d
 
 
 def conv2d(

theano/tensor/nnet/abstract_conv.py

@@ -4,27 +4,33 @@ Abstract conv interface
 
 
 import logging
-from six import reraise, integer_types
 import sys
 
+from six import integer_types, reraise
+
+
 try:
     from math import gcd
 except ImportError:
     from fractions import gcd
 
-import theano
+import warnings
 
-from theano.tensor import as_tensor_variable, patternbroadcast
-from theano.tensor import get_scalar_constant_value, NotScalarConstantError
-from theano.tensor.opt import Assert
-from theano.gof import Apply, Op
+import numpy as np
 
+import theano
+from theano.gof import Apply, Op
+from theano.tensor.basic import (
+    NotScalarConstantError,
+    as_tensor_variable,
+    get_scalar_constant_value,
+    patternbroadcast,
+)
+from theano.tensor.opt import Assert
 
-import warnings
-import numpy as np
 
 try:
-    from scipy.signal.signaltools import _valfrommode, _bvalfromboundary, convolve
+    from scipy.signal.signaltools import _bvalfromboundary, _valfrommode, convolve
     from scipy.signal.sigtools import _convolve2d
 
     imported_scipy_signal = True

theano/tensor/nnet/blocksparse.py

 import numpy as np
 
 import theano
-from theano import Op, Apply
-from theano.tensor import discrete_dtypes
+from theano.gof.graph import Apply
+from theano.gof.op import Op
 from theano.gradient import grad_undefined
+from theano.tensor.basic import discrete_dtypes
 
 
 class SparseBlockGemv(Op):

theano/tensor/nnet/bn.py

 import numpy as np
 
 import theano
-
-# import theano.tensor.basic as tt
-
-from theano import Apply, Op
-from theano.gof import local_optimizer
-from theano.gof.opt import copy_stack_trace
+from theano.gof.graph import Apply
+from theano.gof.op import Op
+from theano.gof.opt import copy_stack_trace, local_optimizer
 from theano.scalar import Composite, add, as_common_dtype, mul, sub, true_div
 
 # Work-around for Python 3.6 issue that prevents `import theano.tensor as tt`
 from theano.tensor import basic as tt
-from theano.tensor import TensorType, as_tensor_variable
+from theano.tensor.basic import as_tensor_variable
 from theano.tensor.elemwise import Elemwise
 from theano.tensor.opt import register_specialize_device
+from theano.tensor.type import TensorType
 
 
 class BNComposite(Composite):

theano/tensor/nnet/conv.py

@@ -10,27 +10,27 @@ See especially conv2d().
 
 
 import logging
+import warnings
 
 import numpy as np
 
-import warnings
-
 import theano
-from theano import OpenMPOp
-from theano.tensor import (
+from theano.gof.graph import Apply
+from theano.gof.op import OpenMPOp
+from theano.tensor import blas
+from theano.tensor.basic import (
+    NotScalarConstantError,
     as_tensor_variable,
-    blas,
     get_scalar_constant_value,
     patternbroadcast,
-    NotScalarConstantError,
 )
-from theano.gof import Apply
 from theano.tensor.nnet.abstract_conv import get_conv_output_shape, get_conv_shape_1axis
 
+
 try:
     # TODO: move these back out to global scope when they no longer
     # cause an atexit error
-    from scipy.signal.signaltools import _valfrommode, _bvalfromboundary
+    from scipy.signal.signaltools import _bvalfromboundary, _valfrommode
     from scipy.signal.sigtools import _convolve2d
 
     imported_scipy_signal = True

theano/tensor/nnet/conv3d2d.py

 import theano
-from theano.gradient import DisconnectedType
-from theano.gof import Op, Apply, TopoOptimizer
-from theano.gof.opt import copy_stack_trace
 from theano import tensor
+from theano.gof import Apply, Op, TopoOptimizer
+from theano.gof.opt import copy_stack_trace
+from theano.gradient import DisconnectedType
 
 
 def get_diagonal_subtensor_view(x, i0, i1):

theano/tensor/nnet/corr.py

-import os
 import logging
+import os
 
 from six import integer_types
 
 import theano
-from theano import Apply
 from theano import gof
-from theano.gof import ParamsType, EnumList
-from theano.scalar import int64, int8
-from theano.tensor import as_tensor_variable, TensorType
-from theano.tensor.nnet.abstract_conv import get_conv_output_shape
+from theano.gof.graph import Apply
+from theano.gof.params_type import ParamsType
+from theano.gof.type import EnumList
+from theano.scalar import int8, int64
 from theano.tensor import blas_headers
-from theano.tensor.blas import ldflags, blas_header_version
+from theano.tensor.basic import as_tensor_variable
+from theano.tensor.blas import blas_header_version, ldflags
+from theano.tensor.nnet.abstract_conv import get_conv_output_shape
+from theano.tensor.type import TensorType
+
 
 _logger = logging.getLogger(__name__)
 

theano/tensor/nnet/corr3d.py

-import os
 import logging
+import os
 
 from six import integer_types
 
 import theano
-from theano import Apply
 from theano import gof
-from theano.gof import ParamsType, EnumList
+from theano.gof.graph import Apply
+from theano.gof.params_type import ParamsType
+from theano.gof.type import EnumList
 from theano.scalar import int64
-from theano.tensor import as_tensor_variable, TensorType
-from theano.tensor.nnet.abstract_conv import get_conv_output_shape
 from theano.tensor import blas_headers
-from theano.tensor.blas import ldflags, blas_header_version
+from theano.tensor.basic import as_tensor_variable
+from theano.tensor.blas import blas_header_version, ldflags
+from theano.tensor.nnet.abstract_conv import get_conv_output_shape
+from theano.tensor.type import TensorType
+
 
 _logger = logging.getLogger(__name__)
 

theano/tensor/nnet/ctc.py

@@ -2,7 +2,6 @@ import os
 import sys
 
 import theano.tensor as tt
-
 from theano import config, gof
 from theano.gof import local_optimizer
 from theano.gof.cmodule import GCC_compiler

theano/tensor/nnet/neighbours.py

@@ -6,7 +6,6 @@ import numpy as np
 
 import theano
 import theano.tensor as tt
-
 from theano import Apply, Op
 from theano.gof import EnumList
 from theano.gradient import grad_not_implemented, grad_undefined

theano/tensor/nnet/nnet.py

@@ -17,35 +17,29 @@ import logging
 import warnings
 
 import numpy as np
-import theano
-
-# import theano.tensor.basic as tt
 
+import theano
 from theano import scalar
 from theano.compile import optdb
 from theano.gof.graph import Apply
 from theano.gof.op import Op
+from theano.gof.opt import copy_stack_trace, local_optimizer, optimizer
+from theano.gradient import DisconnectedType, grad_not_implemented
+from theano.scalar import UnaryScalarOp
 
 # Work-around for Python 3.6 issue that prevents `import theano.tensor as tt`
 from theano.tensor import basic as tt
+from theano.tensor import extra_ops, opt, subtensor
+from theano.tensor.basic import MaxAndArgmax, as_tensor_variable, log
+from theano.tensor.elemwise import Elemwise
+from theano.tensor.nnet.blocksparse import sparse_block_dot
+from theano.tensor.nnet.sigm import sigmoid, softplus
 from theano.tensor.opt import (
+    register_canonicalize,
     register_specialize,
     register_stabilize,
-    register_canonicalize,
 )
-from theano.gof.opt import (
-    optimizer,
-    copy_stack_trace,
-    local_optimizer,
-)
-from theano.gradient import DisconnectedType, grad_not_implemented
-from theano.scalar import UnaryScalarOp
-from theano.tensor import as_tensor_variable, extra_ops, opt, subtensor
-from theano.tensor.elemwise import Elemwise
 from theano.tensor.subtensor import AdvancedSubtensor
-from theano.tensor.basic import log, MaxAndArgmax
-from theano.tensor.nnet.blocksparse import sparse_block_dot
-from theano.tensor.nnet.sigm import sigmoid, softplus
 from theano.tensor.type import values_eq_approx_remove_inf, values_eq_approx_remove_nan
 
 

theano/tensor/nnet/opt.py

@@ -5,38 +5,33 @@ Optimizations addressing the ops in nnet root directory
 import theano
 from theano import compile, gof
 from theano.compile import optdb
-from theano.gof import local_optimizer
-from theano.gof.opt import copy_stack_trace
-
-from theano.tensor.nnet.corr import CorrMM, CorrMM_gradInputs, CorrMM_gradWeights
-from theano.tensor.nnet.corr3d import (
-    Corr3dMM,
-    Corr3dMMGradInputs,
-    Corr3dMMGradWeights,
-)
-from theano.tensor.nnet.blocksparse import (
-    SparseBlockGemv,
-    SparseBlockOuter,
-    sparse_block_gemv_inplace,
-    sparse_block_outer_inplace,
+from theano.gof.opt import (
+    LocalMetaOptimizerSkipAssertionError,
+    copy_stack_trace,
+    local_optimizer,
 )
 from theano.tensor.nnet.abstract_conv import (
     AbstractConv2d,
-    AbstractConv2d_gradWeights,
     AbstractConv2d_gradInputs,
-)
-from theano.tensor.nnet.abstract_conv import (
+    AbstractConv2d_gradWeights,
     AbstractConv3d,
-    AbstractConv3d_gradWeights,
     AbstractConv3d_gradInputs,
+    AbstractConv3d_gradWeights,
+    get_conv_output_shape,
+)
+from theano.tensor.nnet.blocksparse import (
+    SparseBlockGemv,
+    SparseBlockOuter,
+    sparse_block_gemv_inplace,
+    sparse_block_outer_inplace,
 )
-from theano.tensor.nnet.abstract_conv import get_conv_output_shape
-from theano.tensor.opt import register_specialize_device
-from theano.tensor import TensorType
-from theano.tensor import opt
 
 # Cpu implementation
-from theano.tensor.nnet.conv import conv2d, ConvOp
+from theano.tensor.nnet.conv import ConvOp, conv2d
+from theano.tensor.nnet.corr import CorrMM, CorrMM_gradInputs, CorrMM_gradWeights
+from theano.tensor.nnet.corr3d import Corr3dMM, Corr3dMMGradInputs, Corr3dMMGradWeights
+from theano.tensor.opt import in2out, register_specialize_device
+from theano.tensor.type import TensorType
 
 
 @gof.local_optimizer([SparseBlockGemv], inplace=True)
@@ -591,7 +586,7 @@ def local_abstractconv_check(node):
             AbstractConv3d_gradInputs,
         ),
     ):
-        raise gof.opt.LocalMetaOptimizerSkipAssertionError(
+        raise LocalMetaOptimizerSkipAssertionError(
             "%s Theano optimization failed: there is no implementation "
             "available supporting the requested options. Did you exclude "
             'both "conv_dnn" and "conv_gemm" from the optimizer? If on GPU, '
@@ -603,7 +598,7 @@ def local_abstractconv_check(node):
 
 optdb.register(
     "AbstractConvCheck",
-    opt.in2out(local_abstractconv_check, name="AbstractConvCheck"),
+    in2out(local_abstractconv_check, name="AbstractConvCheck"),
     48.7,
     "fast_compile",
     "fast_run",

theano/tensor/nnet/sigm.py

@@ -13,11 +13,13 @@ import numpy as np
 
 import theano
 from theano import config, gof, printing, scalar
+from theano.gof.opt import copy_stack_trace
 from theano.printing import pprint
 from theano.tensor import basic as tensor
-from theano.tensor import elemwise, opt, NotScalarConstantError
+from theano.tensor import elemwise, opt
+from theano.tensor.basic import NotScalarConstantError
 from theano.tensor.type import values_eq_approx_remove_inf
-from theano.gof.opt import copy_stack_trace
+
 
 ############
 #
@@ -155,9 +157,10 @@ class ScalarSigmoid(scalar.UnaryScalarOp):
         val_hard = hard_sigmoid(data).eval()
         val_ultra = ultra_fast_sigmoid(data).eval()
 
-        import matplotlib.pyplot as plt
         import os
 
+        import matplotlib.pyplot as plt
+
         fig = plt.figure()
         ax = fig.add_subplot(111)
         ax.plot(data, val)  # , 'o-')