Index _ | A | B | C | D | E | F | G | H | I | L | M | N | O | P | R | S | T | U | V | W | Z _ __init__() (mygrad.absolute method) (mygrad.add method) (mygrad.arccos method) (mygrad.arccosh method) (mygrad.arcsin method) (mygrad.arcsinh method) (mygrad.arctan method) (mygrad.arctan2 method) (mygrad.arctanh method) (mygrad.cbrt method) (mygrad.cos method) (mygrad.cosh method) (mygrad.exp method) (mygrad.exp2 method) (mygrad.expm1 method) (mygrad.log method) (mygrad.log10 method) (mygrad.log1p method) (mygrad.log2 method) (mygrad.logaddexp method) (mygrad.logaddexp2 method) (mygrad.matmul method) (mygrad.maximum method) (mygrad.minimum method) (mygrad.multiply method) (mygrad.negative method) (mygrad.nnet.activations.tanh method) (mygrad.operation_base.Operation method) (mygrad.positive method) (mygrad.power method) (mygrad.reciprocal method) (mygrad.sin method) (mygrad.sinh method) (mygrad.sqrt method) (mygrad.square method) (mygrad.subtract method) (mygrad.tan method) (mygrad.tanh method) A absolute (class in mygrad) add (class in mygrad) add_sequence() (in module mygrad) amax() (in module mygrad) amin() (in module mygrad) arange() (in module mygrad) arccos (class in mygrad) arccosh (class in mygrad) arcsin (class in mygrad) arcsinh (class in mygrad) arctan (class in mygrad) arctan2 (class in mygrad) arctanh (class in mygrad) asarray() (in module mygrad) astensor() (in module mygrad) astype() (mygrad.Tensor method) atleast_1d() (in module mygrad) atleast_2d() (in module mygrad) atleast_3d() (in module mygrad) B backward() (mygrad.operation_base.Operation method) (mygrad.Tensor method) backward_var() (mygrad.operation_base.Operation method) base (mygrad.Tensor property) batchnorm() (in module mygrad.nnet.layers) broadcast_to() (in module mygrad) build_graph() (in module mygrad.computational_graph) C cbrt (class in mygrad) clear_graph() (mygrad.Tensor method) clip() (in module mygrad) concatenate() (in module mygrad) constant (mygrad.Tensor property) conv_nd() (in module mygrad.nnet.layers) copy() (mygrad.Tensor method) cos (class in mygrad) cosh (class in mygrad) creator (mygrad.Tensor property) cumprod() (in module mygrad) cumsum() (in module mygrad) D dirac() (in module mygrad.nnet.initializers) divide (in module mygrad) dtype (mygrad.Tensor property) E einsum() (in module mygrad) elu() (in module mygrad.nnet.activations) empty() (in module mygrad) empty_like() (in module mygrad) exp (class in mygrad) exp2 (class in mygrad) expand_dims() (in module mygrad) expm1 (class in mygrad) eye() (in module mygrad) F flatten() (mygrad.Tensor method) focal_loss() (in module mygrad.nnet.losses) full() (in module mygrad) full_like() (in module mygrad) G geomspace() (in module mygrad) glorot_normal() (in module mygrad.nnet.initializers) glorot_uniform() (in module mygrad.nnet.initializers) glu() (in module mygrad.nnet.activations) grad (mygrad.Tensor property) gru() (in module mygrad.nnet.layers) H hard_tanh() (in module mygrad.nnet.activations) he_normal() (in module mygrad.nnet.initializers) he_uniform() (in module mygrad.nnet.initializers) I identity() (in module mygrad) item() (mygrad.Tensor method) L leaky_relu() (in module mygrad.nnet.activations) linspace() (in module mygrad) load() (in module mygrad) log (class in mygrad) log10 (class in mygrad) log1p (class in mygrad) log2 (class in mygrad) logaddexp (class in mygrad) logaddexp2 (class in mygrad) logsoftmax() (in module mygrad.nnet.activations) logspace() (in module mygrad) M margin_ranking_loss() (in module mygrad.nnet.losses) matmul (class in mygrad) max() (in module mygrad) max_pool() (in module mygrad.nnet.layers) maximum (class in mygrad) mean() (in module mygrad) mem_guard_off (in module mygrad) mem_guard_on (in module mygrad) min() (in module mygrad) minimum (class in mygrad) moveaxis() (in module mygrad) multi_matmul() (in module mygrad) multiclass_hinge() (in module mygrad.nnet.losses) multiply (class in mygrad) multiply_sequence() (in module mygrad) N ndim (mygrad.Tensor property) negative (class in mygrad) negative_log_likelihood() (in module mygrad.nnet.losses) no_autodiff (in module mygrad) norm() (in module mygrad.linalg) normal() (in module mygrad.nnet.initializers) null_grad() (mygrad.Tensor method) null_gradients() (mygrad.Tensor method) O ones() (in module mygrad) ones_like() (in module mygrad) Operation (class in mygrad.operation_base) P positive (class in mygrad) power (class in mygrad) prod() (in module mygrad) R rand() (in module mygrad.random) randint() (in module mygrad.random) randn() (in module mygrad.random) random() (in module mygrad.random) random_sample() (in module mygrad.random) ranf() (in module mygrad.random) ravel() (in module mygrad) reciprocal (class in mygrad) relu() (in module mygrad.nnet.activations) repeat() (in module mygrad) reshape() (in module mygrad) roll() (in module mygrad) S sample() (in module mygrad.random) save() (in module mygrad) seed() (in module mygrad.random) selu() (in module mygrad.nnet.activations) shape (mygrad.Tensor property) sigmoid() (in module mygrad.nnet.activations) sin (class in mygrad) sinc() (in module mygrad) sinh (class in mygrad) size (mygrad.Tensor property) sliding_window_view() (in module mygrad) soft_sign() (in module mygrad.nnet.activations) softmax() (in module mygrad.nnet.activations) softmax_crossentropy() (in module mygrad.nnet.losses) softmax_focal_loss() (in module mygrad.nnet.losses) sqrt (class in mygrad) square (class in mygrad) squeeze() (in module mygrad) stack() (in module mygrad) std() (in module mygrad) subtract (class in mygrad) sum() (in module mygrad) swapaxes() (in module mygrad) T T (mygrad.Tensor property) tan (class in mygrad) tanh (class in mygrad) (class in mygrad.nnet.activations) tensor() (in module mygrad) transpose() (in module mygrad) turn_memory_guarding_off() (in module mygrad) U uniform() (in module mygrad.nnet.initializers) V var() (in module mygrad) W where() (in module mygrad) Z zeros() (in module mygrad) zeros_like() (in module mygrad)