move LoadFromDisk op to new io.py file

theano/tensor/basic.py

@@ -2021,60 +2021,6 @@ def cast(x, dtype):
             'imag(), angle() or abs()'))
     return _cast_mapping[dtype](x)
 
-##########################
-# Disk Access
-##########################
-
-class LoadFromDisk(Op):
-    """
-    An operation to load an array from disk
-
-    See Also
-        load
-
-    @note: Non-differentiable.
-    """
-    def __init__(self, dtype, broadcastable):
-        self.dtype = dtype
-        self.broadcastable = broadcastable
-
-    def __eq__(self, other):
-        return (type(self) == type(other) and
-                self.broadcastable == other.broadcastable and
-                self.dtype == other.dtype)
-
-    def __hash__(self):
-        return hash((type(self), self.dtype, self.broadcastable))
-
-    def make_node(self, path):
-        if isinstance(path, str):
-            path = Constant(Generic(), path)
-        return gof.Apply(self, [path], [tensor(self.dtype,
-                                        broadcastable=self.broadcastable)])
-
-    def perform(self, node, inp, out):
-        path = inp[0]
-        d = numpy.load(path)
-        out[0][0] = d[d.keys()[0]].astype(self.dtype)
-
-    def __str__(self):
-        return "Load: %s, %s"%(self.dtype, self.broadcastable)
-
-def load(path, dtype, broadcastable):
-    """
-    Load an array from a .npz file
-
-    >>> from theano import *
-    >>> path = Variable(Generic())
-    >>> x = tensor.load(path, 'int64', (False,))
-    >>> y = x*2
-    >>> fn = function([path], y)
-    >>> fn("stored-array.npz")
-    array([0, 2, 4, 6, 8], dtype=int64)
-    """
-
-    return LoadFromDisk(dtype, broadcastable)(path)
-
 ##########################
 # Unary Operations
 ##########################

theano/tensor/io.py

+import numpy
+import theano
+from theano import gof
+from theano.gof import Apply, Constant, Generic, Op, Type, Value, Variable
+from basic import tensor
+##########################
+# Disk Access
+##########################
+
+class LoadFromDisk(Op):
+    """
+    An operation to load an array from disk
+
+    See Also
+        load
+
+    @note: Non-differentiable.
+    """
+    def __init__(self, dtype, broadcastable):
+        self.dtype = dtype
+        self.broadcastable = broadcastable
+
+    def __eq__(self, other):
+        return (type(self) == type(other) and
+                self.broadcastable == other.broadcastable and
+                self.dtype == other.dtype)
+
+    def __hash__(self):
+        return hash((type(self), self.dtype, self.broadcastable))
+
+    def make_node(self, path):
+        if isinstance(path, str):
+            path = Constant(Generic(), path)
+        return gof.Apply(self, [path], [tensor(self.dtype,
+                                        broadcastable=self.broadcastable)])
+
+    def perform(self, node, inp, out):
+        path = inp[0]
+        d = numpy.load(path)
+        out[0][0] = d[d.keys()[0]].astype(self.dtype)
+
+    def __str__(self):
+        return "Load: %s, %s"%(self.dtype, self.broadcastable)
+
+def load(path, dtype, broadcastable):
+    """
+    Load an array from a .npz file
+
+    >>> from theano import *
+    >>> path = Variable(Generic())
+    >>> x = tensor.load(path, 'int64', (False,))
+    >>> y = x*2
+    >>> fn = function([path], y)
+    >>> fn("stored-array.npz")
+    array([0, 2, 4, 6, 8], dtype=int64)
+    """
+
+    return LoadFromDisk(dtype, broadcastable)(path)
+

theano/tensor/tests/test_basic.py

@@ -3964,17 +3964,6 @@ class T_scalarfromtensor(unittest.TestCase):
         self.assertTrue(isinstance(v, numpy.int64))
         self.assertTrue(v.shape == (),v.shape)
 
-class T_load_tensor(unittest.TestCase):
-    def test0(self):
-        data = numpy.arange(5)
-        filename = "_load_tensor_test_1.npz"
-        numpy.savez(filename, data)
-        path = Variable(Generic())
-        x = tensor.load(path, 'int64', (False,))
-        y = x*2
-        fn = function([path], [y])
-        assert (fn(filename) == data*2).all()
-
 class test_grad(unittest.TestCase):
     class O(gof.op.Op):
         def __init__(self):

theano/tensor/tests/test_io.py

+import unittest
+from theano import tensor, function, Variable, Generic
+import numpy
+
+class T_load_tensor(unittest.TestCase):
+    def test0(self):
+        data = numpy.arange(5)
+        filename = "_load_tensor_test_1.npz"
+        numpy.savez(filename, data)
+        path = Variable(Generic())
+        x = tensor.load(path, 'int64', (False,))
+        y = x*2
+        fn = function([path], [y])
+        assert (fn(filename) == data*2).all()
+