| /external/tensorflow/tensorflow/contrib/nn/python/ops/ |
| fwd_gradients.py | 57 dydxs = gradients(ys, xs, grad_ys=us)
74 dysdx = gradients(dydxs, us, grad_ys=grad_xs)
|
| /external/tensorflow/tensorflow/python/ops/ |
| gradients_impl.py | 46 grad_ys=None,
55 `ys` and `xs` are each a `Tensor` or a list of tensors. `grad_ys`
63 `grad_ys` is a list of tensors of the same length as `ys` that holds
64 the initial gradients for each y in `ys`. When `grad_ys` is None,
66 user can provide their own initial `grad_ys` to compute the
123 grad_ys: Optional. A `Tensor` or list of tensors the same size as
156 ys, xs, grad_ys, name, colocate_gradients_with_ops,
165 grad_ys=None,
173 `ys` and `xs` are each a `Tensor` or a list of tensors. `grad_ys`
181 `grad_ys` is a list of tensors of the same length as `ys` that hold
[all...] |
| gradients_util.py | 191 def _DefaultGradYs(grad_ys,
195 """Fill in default values for grad_ys.
198 grad_ys: List of gradients, can contain None.
213 if len(grad_ys) != len(ys):
214 raise ValueError("Passed %d grad_ys for %d ys" % (len(grad_ys), len(ys)))
215 grad_ys = ops.convert_n_to_tensor_or_indexed_slices(grad_ys, name="grad_y")
217 for i in xrange(len(grad_ys)):
218 grad_y = grad_ys[i
[all...] |
| cond_v2.py | 280 grad_ys = []
285 grad_ys.append(grad_y)
292 ys, func_graph.inputs, grad_ys=grad_ys,
|
| while_v2.py | 494 grad_ys = args[3:]
502 ys, xs, grad_ys=grad_ys, src_graph=func_graph,
[all...] |
| gradients_test.py | 240 dx, = gradients.gradients(y, x, grad_ys=dy)
832 r"Gradients of complex tensors must set grad_ys "
[all...] |
| /external/tensorflow/tensorflow/compiler/tests/ |
| tensor_array_ops_test.py | 463 ys=[r0], xs=[value_0], grad_ys=[c([[2.0, 3.0]])])
470 grad_ys=[c([[2.0, 3.0]]), c([[1.0, -1.0]])])
475 ys=[r1], xs=[value_1], grad_ys=[c([[-2.0, -4.0]])])
483 grad_ys=[c([[2.0, 3.0]]), c([[1.0, -1.0]]), c([[-2.0, -10.0]])])
517 grad_ys=[
566 grad_ys=[[2.0, 3.0], [-1.5, 1.5], [4.0, 5.0]])
591 grad_ys=[[[2.0, -2.0], [20.0, -20.0], [200.0, -200.0],
905 grad_r0 = gradients_impl.gradients(ys=[r0], xs=[x], grad_ys=[1.0])
[all...] |
| fft_test.py | 101 grad_ys=array_ops.ones_like(out))
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| tensor_array_ops_test.py | 722 ys=[r0], xs=[value_0], grad_ys=[c([[2.0, 3.0]])])
729 grad_ys=[c([[2.0, 3.0]]), c([[1.0, -1.0]])])
734 ys=[r1], xs=[value_1], grad_ys=[c(-2.0)])
742 grad_ys=[c([[2.0, 3.0]]), c([[1.0, -1.0]]), c(-2.0)])
775 grad_ys=[
838 grad_ys=[[2.0, 3.0], [-1.5, 1.5], [4.0, 5.0]])
[all...] |
| nth_element_op_test.py | 169 values, inputs, grad_ys=[[-1., 2., 5.]]),
|
| topk_op_test.py | 213 values, inputs, grad_ys=[[[1., 2., 3.], [4., 5., 6.]]]),
|
| diag_op_test.py | 202 grads = gradients_impl.gradients(output, [mat, v], grad_ys=grad_input)
|
| array_ops_test.py | [all...] |
| control_flow_ops_py_test.py | [all...] |
| cwise_ops_test.py | [all...] |
| /external/tensorflow/tensorflow/contrib/layers/python/layers/ |
| rev_block_lib.py | 90 def _rev_layer_backward(ys, grad_ys, f, g, f_vars, f_side_input, g_vars,
94 grad_y1, grad_y2 = grad_ys
246 def _efficient_grad_fn(*grad_ys, **kwargs):
298 ys, grad_ys, f_ret, g_ret = _rev_layer_backward(
299 ys, grad_ys, f[i], g[i], f_vars[i], self.f_side_input, g_vars[i],
331 grad_x1, grad_x2 = grad_ys
|
| /external/tensorflow/tensorflow/contrib/recurrent/python/ops/ |
| recurrent.py | 636 grad_ys = _Flatten([dstate1])
637 grads = gradients_impl.gradients(ys=ys, xs=xs, grad_ys=grad_ys)
|
| /external/tensorflow/tensorflow/contrib/recurrent/python/kernel_tests/ |
| recurrent_test.py | 120 ys=[xw], xs=[h0, x, w], grad_ys=[dxw])
|
| /external/tensorflow/tensorflow/contrib/optimizer_v2/ |
| optimizer_v2.py | 821 grad_ys=grad_loss
[all...] |
| /external/tensorflow/tensorflow/python/training/ |
| optimizer.py | 499 loss, var_refs, grad_ys=grad_loss,
[all...] |
| /external/tensorflow/tensorflow/python/eager/ |
| function.py | 777 grad_ys=gradients_wrt_outputs,
[all...] |
| /external/tensorflow/tensorflow/python/framework/ |
| function_test.py | 368 dx, dy = gradients_impl.gradients([z], [x, y], grad_ys=[1.0])
380 # Tests for constant folding of grad_ys
[all...] |
