Merge pull request #231 from arogozhnikov/remove-mxnet

Remove mxnet

einops/_backends.py

@@ -248,70 +248,6 @@ def layers(self):
         return gluon
 
 
-class MXNetBackend(AbstractBackend):
-    framework_name = 'mxnet.symbol'
-
-    def __init__(self):
-        import mxnet
-        self.mx = mxnet
-
-    def is_appropriate_type(self, tensor):
-        return isinstance(tensor, self.mx.symbol.Symbol)
-
-    def create_symbol(self, shape, dtype='float32'):
-        # mxnet accepts zeros as undefined dimensions
-        shape = tuple(0 if d is None else d for d in shape)
-        var = self.mx.symbol.Variable('input', shape=shape, dtype=dtype)
-        return var
-
-    def eval_symbol(self, symbol, input_dict):
-        args = {var.name: self.mx.nd.array(val) for var, val in input_dict}
-        ex = symbol.bind(ctx=self.mx.cpu(), args=args)
-        ex.forward()
-        return ex.outputs[0].asnumpy()
-
-    def shape(self, x):
-        # mxnet has problems with shape inference - it does not provide shape symbols
-        # shape_array seems to be impossible to use in shape inference
-        # infer_shape_partial returns empty tuple if was not able to infer shape
-        # reductions such as sum can't return scalars, but return 1-element vectors
-        shape = x.infer_shape_partial()[1][0]
-        if len(shape) == 0:
-            warnings.warn('mxnet inferred shape to be (), which probably means it could not be inferred')
-        shape = tuple(UnknownSize() if d == 0 else d for d in shape)
-        return shape
-
-    def reshape(self, x, shape):
-        if len(shape) == 0:
-            return x  # poor support of scalars in mxnet
-        if any(isinstance(dimension, UnknownSize) for dimension in shape):
-            from einops import EinopsError
-            raise EinopsError("Mxnet couldn't infer all dimensions statically, please provide those with axes_lengths")
-        return x.reshape(shape)
-
-    def arange(self, start, stop):
-        return self.mx.symbol.arange(start, stop)
-
-    def stack_on_zeroth_dimension(self, tensors: list):
-        return self.mx.symbol.stack(*tensors)
-
-    def tile(self, x, repeats):
-        return self.mx.symbol.tile(x, repeats)
-
-    def concat(self, tensors, axis: int):
-        return self.mx.symbol.concat(tensors, dim=axis)
-
-    def add_axis(self, x, new_position):
-        return self.mx.symbol.expand_dims(x, new_position)
-
-    def is_float_type(self, x):
-        return 'float' in str(x.infer_type()[1][0])
-
-    def layers(self):
-        from .layers import gluon
-        return gluon
-
-
 class TorchBackend(AbstractBackend):
     framework_name = 'torch'
 
@@ -677,4 +613,4 @@ def layers(self):
         return oneflow
 
     def einsum(self, pattern, *x):
-        return self.flow.einsum(pattern, *x)
+        return self.flow.einsum(pattern, *x)

einops/einops.py

@@ -395,7 +395,7 @@ def reduce(tensor: Tensor, pattern: str, reduction: Reduction, **axes_lengths: i
     ```
 
     Parameters:
-        tensor: tensor: tensor of any supported library (e.g. numpy.ndarray, tensorflow, pytorch, mxnet.ndarray).
+        tensor: tensor: tensor of any supported library (e.g. numpy.ndarray, tensorflow, pytorch).
             list of tensors is also accepted, those should be of the same type and shape
         pattern: string, reduction pattern
         reduction: one of available reductions ('min', 'max', 'sum', 'mean', 'prod'), case-sensitive
@@ -467,7 +467,7 @@ def rearrange(tensor: Union[Tensor, List[Tensor]], pattern: str, **axes_lengths)
     Find more examples in einops tutorial.
 
     Parameters:
-        tensor: tensor of any supported library (e.g. numpy.ndarray, tensorflow, pytorch, mxnet.ndarray).
+        tensor: tensor of any supported library (e.g. numpy.ndarray, tensorflow, pytorch).
                 list of tensors is also accepted, those should be of the same type and shape
         pattern: string, rearrangement pattern
         axes_lengths: any additional specifications for dimensions
@@ -521,7 +521,7 @@ def repeat(tensor: Tensor, pattern: str, **axes_lengths) -> Tensor:
     Find more examples in einops tutorial.
 
     Parameters:
-        tensor: tensor of any supported library (e.g. numpy.ndarray, tensorflow, pytorch, mxnet.ndarray).
+        tensor: tensor of any supported library (e.g. numpy.ndarray, tensorflow, pytorch).
             list of tensors is also accepted, those should be of the same type and shape
         pattern: string, rearrangement pattern
         axes_lengths: any additional specifications for dimensions

test.py

@@ -2,7 +2,7 @@
 Usage: python test.py
 1. Installs part of dependencies (make sure `which pip` points to correct location)
 2. Installs current version of einops in editable mode
-3. Runs tests
+3. Runs the tests
 """
 
 import os
@@ -38,7 +38,6 @@ def run(cmd, **env):
 # install dependencies
 dependencies = [
     'numpy',
-    'mxnet==1.*',
     'torch',
     'tensorflow',
     'chainer',
@@ -58,6 +57,7 @@ def run(cmd, **env):
 # oneflow provides wheels for linux, but not mac, so it is tested only on linux
 skip_oneflow = 'linux' not in sys.platform
 skip_oneflow = True
+
 if not skip_oneflow:
     # oneflow installation: https://github.com/Oneflow-Inc/oneflow#install-with-pip-package
     assert 0 == run('pip install -f https://release.oneflow.info oneflow==0.7.0+cpu --user')

tests/__init__.py

@@ -49,12 +49,9 @@ def collect_test_backends(symbolic=False, layers=False):
             ]
     else:
         if not layers:
-            backend_types = [
-                _backends.MXNetBackend,
-            ]
+            backend_types = []
         else:
             backend_types = [
-                _backends.MXNetBackend,
                 _backends.KerasBackend,
             ]
 

tests/test_notebooks.py

@@ -39,7 +39,7 @@ def test_all_notebooks():
 
 def test_dl_notebook_with_all_backends():
     notebook, = Path(__file__).parent.with_name('docs').glob('2-*.ipynb')
-    backends = ['chainer', 'gluon', 'pytorch']
+    backends = ['chainer', 'pytorch']
     if 'tensorflow' in collect_test_backends(symbolic=False, layers=False):
         backends += ['tensorflow']
     for backend in backends:

tests/test_other.py

@@ -41,6 +41,9 @@ def test_backends_installed():
             # instantiate
             backend_type()
         except Exception as e:
+            if 'mxnet' in backend_type.framework_name:
+                # test mxnet only if it is installed. Not complain if not installed
+                continue
             errors.append(e)
     assert len(errors) == 0, errors