def __init__(self, type, data, name=None): Constant.__init__(self, type, data, name) if (isinstance(data, numpy.ndarray) and data.ndim > 0 and len(numpy.unique(data)) == 1): self.tag.unique_value = numpy.unique(data)[0] else: self.tag.unique_value = None
def __init__(self, type, data, name=None): Constant.__init__(self, type, data, name) self.tag.unique_value = None if isinstance(data, numpy.ndarray) and data.ndim > 0: flat_data = data.ravel() if flat_data.shape[0]: if (flat_data == flat_data[0]).all(): self.tag.unique_value = flat_data[0]
def __init__(self, type, data, name=None): Constant.__init__(self, type, data, name) self.tag.unique_value = None if isinstance(data, np.ndarray) and data.ndim > 0: flat_data = data.ravel() if flat_data.shape[0]: if (flat_data == flat_data[0]).all(): self.tag.unique_value = flat_data[0]
def __init__(self, type, data, name=None): assert isinstance(data, slice) # Numpy ndarray aren't hashable, so get rid of them. if isinstance(data.start, numpy.ndarray): assert data.start.ndim == 0 assert "int" in str(data.start.dtype) data = slice(int(data.start), data.stop, data.step) elif isinstance(data.stop, numpy.ndarray): assert data.stop.ndim == 0 assert "int" in str(data.stop.dtype) data = slice(data.start, int(data.stop), data.step) elif isinstance(data.step, numpy.ndarray): assert data.step.ndim == 0 assert "int" in str(data.step.dtype) data = slice(data.start, int(data.stop), data.step) Constant.__init__(self, type, data, name)
def __init__(self, type, data, name=None): assert isinstance(data, slice) # Numpy ndarray aren't hashable, so get rid of them. if isinstance(data.start, np.ndarray): assert data.start.ndim == 0 assert str(data.start.dtype) in theano.tensor.integer_dtypes data = slice(int(data.start), data.stop, data.step) elif isinstance(data.stop, np.ndarray): assert data.stop.ndim == 0 assert str(data.stop.dtype) in theano.tensor.integer_dtypes data = slice(data.start, int(data.stop), data.step) elif isinstance(data.step, np.ndarray): assert data.step.ndim == 0 assert str(data.step.dtype) in theano.tensor.integer_dtypes data = slice(data.start, int(data.stop), data.step) Constant.__init__(self, type, data, name)