def test_sequential_convolution_without_reduction_dim():
c = Convolution(3, init=np.array([4., 2., 1.], dtype=np.float32), sequential=True, pad=False, reduction_rank=0, bias=False)
c.update_signature(Sequence[Tensor[()]]) # input is a sequence of scalars
data = [np.array([2., 6., 4., 8., 6.])] # like a short audio sequence, in the dynamic dimension
out = c(data)
exp = [[24., 40., 38.]]
np.testing.assert_array_equal(out, exp, err_msg='Error in sequential convolution without reduction dimension')
c = Convolution(3, init=np.array([4., 2., 1.], dtype=np.float32), sequential=True, pad=False, reduction_rank=0, bias=False)
c.update_signature(Sequence[Tensor[1]]) # input is a sequence of dim-1 vectors
data = [np.array([[2.], [6], [4.], [8.], [6.]])]
out = c(data)
exp = [[[24.], [40.], [38]]] # not reducing; hence, output is also a sequence of dim-1 vectors
np.testing.assert_array_equal(out, exp, err_msg='Error in sequential convolution without reduction dimension')
# these cases failed before
emb_dim = 10
x = input(**Sequence[Tensor[20]])
m = Embedding(emb_dim)(x)
m = Convolution(filter_shape=3, sequential=True)(m)
# this one still fails
# Reshape: Operand (sub-)dimensions '[3]' incompatible with desired replacement (sub-)dimensions '[]'. Number of elements must be the same..
m = Embedding(emb_dim)(x)
m = reshape(m, (emb_dim,1))
m = Convolution(filter_shape=(3,1), num_filters=13, pad=True, sequential=True)(m)
m = Embedding(emb_dim)(x)
m = Convolution(filter_shape=3, pad=True, sequential=True)(m)
def test_sequential_convolution_without_reduction_dim():
c = Convolution(3, init=np.array([4., 2., 1.], dtype=np.float32), sequential=True, pad=False, reduction_rank=0, bias=False)
c.update_signature(Sequence[Tensor[()]]) # input is a sequence of scalars
data = [np.array([2., 6., 4., 8., 6.])] # like a short audio sequence, in the dynamic dimension
out = c(data)
exp = [[24., 40., 38.]]
np.testing.assert_array_equal(out, exp, err_msg='Error in sequential convolution without reduction dimension')
c = Convolution(3, init=np.array([4., 2., 1.], dtype=np.float32), sequential=True, pad=False, reduction_rank=0, bias=False)
c.update_signature(Sequence[Tensor[1]]) # input is a sequence of dim-1 vectors
data = [np.array([[2.], [6], [4.], [8.], [6.]])]
out = c(data)
exp = [[[24.], [40.], [38]]] # not reducing; hence, output is also a sequence of dim-1 vectors
np.testing.assert_array_equal(out, exp, err_msg='Error in sequential convolution without reduction dimension')
# these cases failed before
emb_dim = 10
x = C.input_variable(**Sequence[Tensor[20]])
m = Embedding(emb_dim)(x)
m = Convolution(filter_shape=3, sequential=True)(m)
# this one still fails
# Reshape: Operand (sub-)dimensions '[3]' incompatible with desired replacement (sub-)dimensions '[]'. Number of elements must be the same..
m = Embedding(emb_dim)(x)
m = reshape(m, (emb_dim,1))
m = Convolution(filter_shape=(3,1), num_filters=13, pad=True, sequential=True)(m)
m = Embedding(emb_dim)(x)
m = Convolution(filter_shape=3, pad=True, sequential=True)(m)
def test_failing_convolution():
with pytest.raises(ValueError):
conv = Convolution((3,3), 1)
conv.update_signature(5)
# BUGBUG: fails with "ValueError: Variable(Plus5_output) with unknown shape detected when compiling the Function graph!"
#print(out)
# ----------------------------------------------
# sequential convolution without reduction dimension
# ----------------------------------------------
from cntk.layers import Convolution
c = Convolution(3,
init=array([4, 2, 1]),
sequential=True,
pad=False,
reduction_rank=0,
bias=False)
dump_function(c)
c.update_signature(1)
dump_function(c)
data = [ # audio sequence
array([[2], [6], [4], [8], [6]])
]
out = c(data)
print(out)
# [[[[ 24. 40. 38.]]]]
# ----------------------------------------------
# 1D convolution without reduction dimension
# ----------------------------------------------
from cntk.layers import Convolution
c = Convolution(3,
init=array([4, 2, 1]),
def test_failing_convolution():
with pytest.raises(ValueError):
conv = Convolution((3,3), 1)
conv.update_signature(5)
debughelpers.dump_function(r)
data = [ # simple sequence
array([[2], [6], [4], [8], [6]])
]
#out = r(data)
# BUGBUG: fails with "ValueError: Variable(Plus5_output) with unknown shape detected when compiling the Function graph!"
#print(out)
# ----------------------------------------------
# sequential convolution without reduction dimension
# ----------------------------------------------
from cntk.layers import Convolution
c = Convolution(3, init=array([4, 2, 1]), sequential=True, pad=False, reduction_rank=0, bias=False)
debughelpers.dump_function(c)
c.update_signature(1)
debughelpers.dump_function(c)
data = [ # audio sequence
array([[2], [6], [4], [8], [6]])
]
out = c(data)
print(out)
# [[[[ 24. 40. 38.]]]]
# ----------------------------------------------
# 1D convolution without reduction dimension
# ----------------------------------------------
from cntk.layers import Convolution
c = Convolution(3, init=array([4, 2, 1]), pad=True, reduction_rank=0, bias=False)
# BUGBUG: pad seems ignored??