Rename theano.tensor.nnet.nnet to theano.tensor.nnet.basic

doc/library/tensor/nnet/nnet.txt → doc/library/tensor/nnet/basic.txt

-.. _libdoc_tensor_nnet_nnet:
+.. _libdoc_tensor_nnet_basic:
 
 ======================================================
-:mod:`nnet` -- Ops for neural networks
+:mod:`basic` -- Basic Ops for neural networks
 ======================================================
 
-.. module:: theano.tensor.nnet.nnet
+.. module:: theano.tensor.nnet.basic
    :platform: Unix, Windows
    :synopsis: Ops for neural networks
 .. moduleauthor:: LISA

tests/tensor/nnet/test_nnet.py → tests/tensor/nnet/test_basic.py

@@ -16,7 +16,7 @@ from theano.graph.fg import FunctionGraph
 from theano.graph.opt import check_stack_trace
 from theano.tensor.basic import Argmax
 from theano.tensor.elemwise import CAReduce, DimShuffle, Elemwise
-from theano.tensor.nnet.nnet import (
+from theano.tensor.nnet.basic import (
     CrossentropyCategorical1Hot,
     CrossentropyCategorical1HotGrad,
     CrossentropySoftmax1HotWithBiasDx,

tests/tensor/test_mlp.py

@@ -12,7 +12,7 @@ import numpy as np
 
 import theano
 import theano.tensor as tt
-from theano.tensor.nnet.nnet import CrossentropySoftmax1HotWithBiasDx, softmax
+from theano.tensor.nnet.basic import CrossentropySoftmax1HotWithBiasDx, softmax
 from theano.tensor.type import ivector, lscalar, matrix
 
 

theano/compile/profiling.py

@@ -1696,7 +1696,7 @@ class ProfileStats:
         # tip 7
         import theano.gpuarray
         import theano.tensor.signal.pool as pool
-        from theano.tensor.nnet.nnet import LogSoftmax
+        from theano.tensor.nnet.basic import LogSoftmax
 
         for (fgraph, a) in self.apply_time:
             node = a

theano/configdefaults.py

@@ -1465,7 +1465,7 @@ def add_deprecated_configvars():
         "warn__argmax_pushdown_bug",
         (
             "Warn if in past version of Theano we generated a bug with the "
-            "theano.tensor.nnet.nnet.local_argmax_pushdown optimization. "
+            "theano.tensor.nnet.basic.local_argmax_pushdown optimization. "
             "Was fixed 27 may 2010"
         ),
         BoolParam(_warn_default("0.3")),

theano/gpuarray/dnn_opt.py

@@ -62,7 +62,7 @@ from theano.tensor.nnet.abstract_conv import (
     assert_conv_shape,
     get_conv_output_shape,
 )
-from theano.tensor.nnet.nnet import LogSoftmax, SoftmaxGrad
+from theano.tensor.nnet.basic import LogSoftmax, SoftmaxGrad
 from theano.tensor.signal.pool import AveragePoolGrad, MaxPoolGrad, Pool
 
 

theano/gpuarray/opt.py

@@ -1480,9 +1480,9 @@ def local_gpua_tri(fgraph, op, context_name, inputs, outputs):
 
 
 @register_opt("fast_compile")
-@op_lifter([theano.tensor.nnet.nnet.CrossentropySoftmaxArgmax1HotWithBias])
+@op_lifter([theano.tensor.nnet.basic.CrossentropySoftmaxArgmax1HotWithBias])
 @register_opt2(
-    [theano.tensor.nnet.nnet.CrossentropySoftmaxArgmax1HotWithBias], "fast_compile"
+    [theano.tensor.nnet.basic.CrossentropySoftmaxArgmax1HotWithBias], "fast_compile"
 )
 def local_gpua_crossentropysoftmaxargmax1hotwithbias(
     fgraph, op, context_name, inputs, outputs
@@ -1491,9 +1491,9 @@ def local_gpua_crossentropysoftmaxargmax1hotwithbias(
 
 
 @register_opt("fast_compile")
-@op_lifter([theano.tensor.nnet.nnet.CrossentropySoftmax1HotWithBiasDx])
+@op_lifter([theano.tensor.nnet.basic.CrossentropySoftmax1HotWithBiasDx])
 @register_opt2(
-    [theano.tensor.nnet.nnet.CrossentropySoftmax1HotWithBiasDx], "fast_compile"
+    [theano.tensor.nnet.basic.CrossentropySoftmax1HotWithBiasDx], "fast_compile"
 )
 def local_gpua_crossentropysoftmax1hotwithbiasdx(
     fgraph, op, context_name, inputs, outputs
@@ -1502,22 +1502,22 @@ def local_gpua_crossentropysoftmax1hotwithbiasdx(
 
 
 @register_opt("fast_compile")
-@op_lifter([theano.tensor.nnet.nnet.Softmax])
-@register_opt2([theano.tensor.nnet.nnet.Softmax], "fast_compile")
+@op_lifter([theano.tensor.nnet.basic.Softmax])
+@register_opt2([theano.tensor.nnet.basic.Softmax], "fast_compile")
 def local_gpua_softmax(fgraph, op, context_name, inputs, outputs):
     return gpu_softmax
 
 
 @register_opt("fast_compile")
-@op_lifter([theano.tensor.nnet.nnet.SoftmaxWithBias])
-@register_opt2([theano.tensor.nnet.nnet.SoftmaxWithBias], "fast_compile")
+@op_lifter([theano.tensor.nnet.basic.SoftmaxWithBias])
+@register_opt2([theano.tensor.nnet.basic.SoftmaxWithBias], "fast_compile")
 def local_gpua_softmaxwithbias(fgraph, op, context_name, inputs, outputs):
     return gpu_softmax_with_bias
 
 
 @register_opt("fast_compile")
-@op_lifter([theano.tensor.nnet.nnet.CrossentropyCategorical1Hot])
-@register_opt2([theano.tensor.nnet.nnet.CrossentropyCategorical1Hot], "fast_compile")
+@op_lifter([theano.tensor.nnet.basic.CrossentropyCategorical1Hot])
+@register_opt2([theano.tensor.nnet.basic.CrossentropyCategorical1Hot], "fast_compile")
 def local_gpu_crossentropycategorical1hot(fgraph, op, context_name, inputs, outputs):
     # There is no corresponding GPU Op, but we can express it as:
     #   coding, one_of_n = inputs
@@ -1528,9 +1528,9 @@ def local_gpu_crossentropycategorical1hot(fgraph, op, context_name, inputs, outp
 
 
 @register_opt("fast_compile")
-@op_lifter([theano.tensor.nnet.nnet.CrossentropyCategorical1HotGrad])
+@op_lifter([theano.tensor.nnet.basic.CrossentropyCategorical1HotGrad])
 @register_opt2(
-    [theano.tensor.nnet.nnet.CrossentropyCategorical1HotGrad], "fast_compile"
+    [theano.tensor.nnet.basic.CrossentropyCategorical1HotGrad], "fast_compile"
 )
 def local_gpu_crossentropycategorical1hotgrad(
     fgraph, op, context_name, inputs, outputs

theano/link/jax/jax_dispatch.py

@@ -57,7 +57,7 @@ from theano.tensor.nlinalg import (
     QRFull,
     QRIncomplete,
 )
-from theano.tensor.nnet.nnet import Softmax
+from theano.tensor.nnet.basic import Softmax
 from theano.tensor.nnet.sigm import ScalarSoftplus
 from theano.tensor.opt import MakeVector
 from theano.tensor.slinalg import Cholesky, Solve

theano/tensor/nnet/__init__.py

@@ -7,8 +7,7 @@ from theano.tensor.nnet.abstract_conv import (
     conv3d,
     separable_conv2d,
 )
-from theano.tensor.nnet.bn import batch_normalization
-from theano.tensor.nnet.nnet import (
+from theano.tensor.nnet.basic import (
     binary_crossentropy,
     categorical_crossentropy,
     confusion_matrix,
@@ -41,6 +40,7 @@ from theano.tensor.nnet.nnet import (
     softmax_with_bias,
     softsign,
 )
+from theano.tensor.nnet.bn import batch_normalization
 from theano.tensor.nnet.sigm import (
     hard_sigmoid,
     scalar_sigmoid,

theano/tensor/nnet/nnet.py → theano/tensor/nnet/basic.py

@@ -926,7 +926,7 @@ def local_softmax_with_bias(fgraph, node):
 
                 if sm_bias.type == node.outputs[0].type:
                     # This condition is not always true. See the test
-                    # nnet/tests/test_nnet.py:T_SoftmaxWithBias.test_broadcast
+                    # nnet/tests/test_basic.py:T_SoftmaxWithBias.test_broadcast
                     return [sm_bias]
 
 
@@ -1672,7 +1672,7 @@ def local_argmax_pushdown(fgraph, node):
         )
     ):
         if config.warn__argmax_pushdown_bug:
-            logging.getLogger("theano.tensor.nnet.nnet").warn(
+            logging.getLogger("theano.tensor.nnet.basic").warn(
                 "There was a bug in Theano fixed on May 27th, 2010 in this case."
                 " I.E. when we take the max of a softplus, softmax, exp, "
                 "log, tanh, sigmoid, softmax_with_bias op, we were doing "