def tensordot(a, b, axes=2):
'''Tensor dot product of two arrays
'''
if isinstance(axes, int):
bx = range(axes)
ao = a.getRank() - axes
ax = [ ao + i for i in bx ]
else:
t = type(axes)
if t is _types.ListType or t is _types.TupleType:
if len(axes) == 0:
raise ValueError, "Given axes sequence should be non-empty"
if len(axes) == 1:
ax = axes[0]
bx = axes[0]
else:
ax = axes[0]
bx = axes[1]
ta = type(ax)
tal = ta is _types.ListType or ta is _types.TupleType
tb = type(bx)
tbl = tb is _types.ListType or tb is _types.TupleType
if tal != tbl:
if tal:
bx = list(bx)
else:
ax = list(ax)
else:
raise ValueError, "Given axes has wrong type"
return _linalg.tensorDotProduct(a, b, ax, bx)
def tensordot(a, b, axes=2):
'''Tensor dot product of two arrays
'''
if isinstance(axes, int):
bx = list(range(axes))
ao = a.getRank() - axes
ax = [ao + i for i in bx]
else:
if isinstance(axes, (list, tuple)):
if len(axes) == 0:
raise ValueError("Given axes sequence should be non-empty")
if len(axes) == 1:
ax = axes[0]
bx = axes[0]
else:
ax = axes[0]
bx = axes[1]
tal = isinstance(ax, (list, tuple))
tbl = isinstance(bx, (list, tuple))
if tal != tbl:
if tal:
bx = list(bx)
else:
ax = list(ax)
else:
raise ValueError("Given axes has wrong type")
return _linalg.tensorDotProduct(a, b, ax, bx)
def tensordot(a, b, axes=2):
'''Tensor dot product of two arrays
'''
if isinstance(axes, int):
bx = range(axes)
ao = a.getRank() - axes
ax = [ ao + i for i in bx ]
else:
t = type(axes)
if t is _types.ListType or t is _types.TupleType:
if len(axes) == 0:
raise ValueError, "Given axes sequence should be non-empty"
if len(axes) == 1:
ax = axes[0]
bx = axes[0]
else:
ax = axes[0]
bx = axes[1]
ta = type(ax)
tal = ta is _types.ListType or ta is _types.TupleType
tb = type(bx)
tbl = tb is _types.ListType or tb is _types.TupleType
if tal != tbl:
if tal:
bx = list(bx)
else:
ax = list(ax)
else:
raise ValueError, "Given axes has wrong type"
return _linalg.tensorDotProduct(a, b, ax, bx)
def inner(a, b):
'''Inner product of two arrays (sum product over last dimensions)'''
return _linalg.tensorDotProduct(a, b, -1, -1)
def inner(a, b):
'''Inner product of two arrays (sum product over last dimensions)'''
return _linalg.tensorDotProduct(a, b, -1, -1)
