def forward_gpu(self, x):
self.y = cuda.empty_like(x[0])
if cudnn.enabled and self.use_cudnn:
handle = cudnn.get_default_handle()
desc = cudnn.get_tensor_desc(x[0], 1, 1)
libcudnn.cudnnActivationForward(
handle, _mode, 1, desc.value, cudnn.get_ptr(x[0]), 0, desc.value, cudnn.get_ptr(self.y)
)
else:
cuda.elementwise("float* y, const float* x", "y[i] = tanhf(x[i])", "tanh_fwd")(self.y, x[0])
return (self.y,)
def forward_gpu(self, x):
self.y = cuda.empty_like(x[0])
if cudnn.enabled and self.use_cudnn:
handle = cudnn.get_default_handle()
desc = cudnn.get_tensor_desc(x[0], 1, 1)
libcudnn.cudnnActivationForward(handle, _mode, 1, desc.value,
cudnn.get_ptr(x[0]), 0, desc.value,
cudnn.get_ptr(self.y))
else:
cuda.elementwise('float* y, const float* x', 'y[i] = tanhf(x[i])',
'tanh_fwd')(self.y, x[0])
return self.y,
def forward_gpu(self, x):
self.y = cuda.empty_like(x[0])
if cudnn.enabled and self.use_cudnn:
handle = cudnn.get_default_handle()
desc = cudnn.get_tensor_desc(x[0], 1, 1)
libcudnn.cudnnActivationForward(
handle, _mode, 1, desc.value, cudnn.get_ptr(x[0]),
0, desc.value, cudnn.get_ptr(self.y))
else:
cuda.elementwise(
'float* y, const float* x', 'y[i] = 1 / (1 + __expf(-x[i]))',
'sigmoid_fwd')(self.y, x[0])
return self.y,
def forward_gpu(self, x):
y = cuda.empty_like(x[0])
if cudnn.enabled and self.use_cudnn:
handle = cudnn.get_default_handle()
desc = cudnn.get_tensor_desc(x[0], 1, 1)
libcudnn.cudnnActivationForward(
handle, _mode, 1, desc.value, cudnn.get_ptr(x[0]),
0, desc.value, cudnn.get_ptr(y))
self.y = y
else:
cuda.elementwise('float* y, const float* x', 'y[i] = max(0.f, x[i])',
'relu_fwd')(y, x[0])
return y,