static Tensor |
torch.__and__(Tensor self,
Scalar other) |
static Tensor |
torch.__lshift___out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.__lshift___outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.__lshift__(Tensor self,
Scalar other) |
static Tensor |
torch.__or__(Tensor self,
Scalar other) |
static Tensor |
torch.__rshift___out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.__rshift___outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.__rshift__(Tensor self,
Scalar other) |
static Tensor |
torch.__xor__(Tensor self,
Scalar other) |
static Tensor |
torch._fill(Tensor self,
Scalar value) |
static Tensor |
torch.add_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.add_out(Tensor out,
Tensor self,
Scalar other,
Scalar alpha) |
static Tensor |
torch.add_out(Tensor out,
Tensor self,
Tensor other,
Scalar alpha) |
static Tensor |
torch.add_outf(Tensor self,
Scalar other,
Scalar alpha,
Tensor out) |
static Tensor |
torch.add_outf(Tensor self,
Tensor other,
Scalar alpha,
Tensor out) |
static Tensor |
torch.add(Scalar x,
Tensor y) |
static Tensor |
torch.add(Tensor self,
Scalar other) |
static Tensor |
torch.add(Tensor self,
Scalar other,
Scalar alpha) |
static Tensor |
torch.add(Tensor self,
Tensor other,
Scalar alpha) |
static Tensor |
torch.addbmm_out(Tensor out,
Tensor self,
Tensor batch1,
Tensor batch2,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.addbmm_outf(Tensor self,
Tensor batch1,
Tensor batch2,
Scalar beta,
Scalar alpha,
Tensor out) |
static Tensor |
torch.addbmm(Tensor self,
Tensor batch1,
Tensor batch2,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.addcdiv_out(Tensor out,
Tensor self,
Tensor tensor1,
Tensor tensor2,
Scalar value) |
static Tensor |
torch.addcdiv_outf(Tensor self,
Tensor tensor1,
Tensor tensor2,
Scalar value,
Tensor out) |
static Tensor |
torch.addcdiv(Tensor self,
Tensor tensor1,
Tensor tensor2,
Scalar value) |
static Tensor |
torch.addcmul_out(Tensor out,
Tensor self,
Tensor tensor1,
Tensor tensor2,
Scalar value) |
static Tensor |
torch.addcmul_outf(Tensor self,
Tensor tensor1,
Tensor tensor2,
Scalar value,
Tensor out) |
static Tensor |
torch.addcmul(Tensor self,
Tensor tensor1,
Tensor tensor2,
Scalar value) |
static Tensor |
torch.addmm_out(Tensor out,
Tensor self,
Tensor mat1,
Tensor mat2,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.addmm_outf(Tensor self,
Tensor mat1,
Tensor mat2,
Scalar beta,
Scalar alpha,
Tensor out) |
static Tensor |
torch.addmm(Tensor self,
Tensor mat1,
Tensor mat2,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.addmv_(Tensor self,
Tensor mat,
Tensor vec,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.addmv_out(Tensor out,
Tensor self,
Tensor mat,
Tensor vec,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.addmv_outf(Tensor self,
Tensor mat,
Tensor vec,
Scalar beta,
Scalar alpha,
Tensor out) |
static Tensor |
torch.addmv(Tensor self,
Tensor mat,
Tensor vec,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.addr_out(Tensor out,
Tensor self,
Tensor vec1,
Tensor vec2,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.addr_outf(Tensor self,
Tensor vec1,
Tensor vec2,
Scalar beta,
Scalar alpha,
Tensor out) |
static Tensor |
torch.addr(Tensor self,
Tensor vec1,
Tensor vec2,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.and(Scalar x,
Tensor y) |
static Tensor |
torch.and(Tensor x,
Scalar y) |
static Tensor |
torch.arange_out(Tensor out,
Scalar end) |
static Tensor |
torch.arange_out(Tensor out,
Scalar start,
Scalar end,
Scalar step) |
static Tensor |
torch.arange_outf(Scalar start,
Scalar end,
Scalar step,
Tensor out) |
static Tensor |
torch.arange_outf(Scalar end,
Tensor out) |
static Tensor |
torch.arange(Scalar end) |
static Tensor |
torch.arange(Scalar start,
Scalar end) |
static Tensor |
torch.arange(Scalar start,
Scalar end,
Scalar step) |
static Tensor |
torch.arange(Scalar start,
Scalar end,
Scalar step,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.arange(Scalar start,
Scalar end,
Scalar step,
TensorOptions options) |
static Tensor |
torch.arange(Scalar start,
Scalar end,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.arange(Scalar start,
Scalar end,
TensorOptions options) |
static Tensor |
torch.arange(Scalar end,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.arange(Scalar end,
TensorOptions options) |
static Tensor |
torch.baddbmm_out(Tensor out,
Tensor self,
Tensor batch1,
Tensor batch2,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.baddbmm_outf(Tensor self,
Tensor batch1,
Tensor batch2,
Scalar beta,
Scalar alpha,
Tensor out) |
static Tensor |
torch.baddbmm(Tensor self,
Tensor batch1,
Tensor batch2,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.bitwise_and_out(Tensor out,
Scalar self,
Tensor other) |
static Tensor |
torch.bitwise_and_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.bitwise_and_outf(Scalar self,
Tensor other,
Tensor out) |
static Tensor |
torch.bitwise_and_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.bitwise_and(Scalar self,
Tensor other) |
static Tensor |
torch.bitwise_and(Tensor self,
Scalar other) |
static Tensor |
torch.bitwise_left_shift_out(Tensor out,
Scalar self,
Tensor other) |
static Tensor |
torch.bitwise_left_shift_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.bitwise_left_shift_outf(Scalar self,
Tensor other,
Tensor out) |
static Tensor |
torch.bitwise_left_shift_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.bitwise_left_shift(Scalar self,
Tensor other) |
static Tensor |
torch.bitwise_left_shift(Tensor self,
Scalar other) |
static Tensor |
torch.bitwise_or_out(Tensor out,
Scalar self,
Tensor other) |
static Tensor |
torch.bitwise_or_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.bitwise_or_outf(Scalar self,
Tensor other,
Tensor out) |
static Tensor |
torch.bitwise_or_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.bitwise_or(Scalar self,
Tensor other) |
static Tensor |
torch.bitwise_or(Tensor self,
Scalar other) |
static Tensor |
torch.bitwise_right_shift_out(Tensor out,
Scalar self,
Tensor other) |
static Tensor |
torch.bitwise_right_shift_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.bitwise_right_shift_outf(Scalar self,
Tensor other,
Tensor out) |
static Tensor |
torch.bitwise_right_shift_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.bitwise_right_shift(Scalar self,
Tensor other) |
static Tensor |
torch.bitwise_right_shift(Tensor self,
Scalar other) |
static Tensor |
torch.bitwise_xor_out(Tensor out,
Scalar self,
Tensor other) |
static Tensor |
torch.bitwise_xor_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.bitwise_xor_outf(Scalar self,
Tensor other,
Tensor out) |
static Tensor |
torch.bitwise_xor_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.bitwise_xor(Scalar self,
Tensor other) |
static Tensor |
torch.bitwise_xor(Tensor self,
Scalar other) |
static Tensor |
torch.bucketize_out(Tensor out,
Scalar self,
Tensor boundaries) |
static Tensor |
torch.bucketize_out(Tensor out,
Scalar self,
Tensor boundaries,
boolean out_int32,
boolean right) |
static Tensor |
torch.bucketize_outf(Scalar self,
Tensor boundaries,
boolean out_int32,
boolean right,
Tensor out) |
static Tensor |
torch.bucketize(Scalar self,
Tensor boundaries) |
static Tensor |
torch.bucketize(Scalar self,
Tensor boundaries,
boolean out_int32,
boolean right) |
static Tensor |
torch.celu_(Tensor self,
Scalar alpha) |
static Tensor |
torch.celu_out(Tensor out,
Tensor self,
Scalar alpha) |
static Tensor |
torch.celu_outf(Tensor self,
Scalar alpha,
Tensor out) |
static Tensor |
torch.celu(Tensor self,
Scalar alpha) |
static Tensor |
torch.chebyshev_polynomial_t_out(Tensor output,
Scalar x,
Tensor n) |
static Tensor |
torch.chebyshev_polynomial_t_out(Tensor output,
Tensor x,
Scalar n) |
static Tensor |
torch.chebyshev_polynomial_t(Scalar x,
Tensor n) |
static Tensor |
torch.chebyshev_polynomial_t(Tensor x,
Scalar n) |
static Tensor |
torch.chebyshev_polynomial_u_out(Tensor output,
Scalar x,
Tensor n) |
static Tensor |
torch.chebyshev_polynomial_u_out(Tensor output,
Tensor x,
Scalar n) |
static Tensor |
torch.chebyshev_polynomial_u(Scalar x,
Tensor n) |
static Tensor |
torch.chebyshev_polynomial_u(Tensor x,
Scalar n) |
static Tensor |
torch.chebyshev_polynomial_v_out(Tensor output,
Scalar x,
Tensor n) |
static Tensor |
torch.chebyshev_polynomial_v_out(Tensor output,
Tensor x,
Scalar n) |
static Tensor |
torch.chebyshev_polynomial_v(Scalar x,
Tensor n) |
static Tensor |
torch.chebyshev_polynomial_v(Tensor x,
Scalar n) |
static Tensor |
torch.chebyshev_polynomial_w_out(Tensor output,
Scalar x,
Tensor n) |
static Tensor |
torch.chebyshev_polynomial_w_out(Tensor output,
Tensor x,
Scalar n) |
static Tensor |
torch.chebyshev_polynomial_w(Scalar x,
Tensor n) |
static Tensor |
torch.chebyshev_polynomial_w(Tensor x,
Scalar n) |
static Tensor |
torch.clamp_max_(Tensor self,
Scalar max) |
static Tensor |
torch.clamp_max_out(Tensor out,
Tensor self,
Scalar max) |
static Tensor |
torch.clamp_max_outf(Tensor self,
Scalar max,
Tensor out) |
static Tensor |
torch.clamp_max(Tensor self,
Scalar max) |
static Tensor |
torch.clamp_min_(Tensor self,
Scalar min) |
static Tensor |
torch.clamp_min_out(Tensor out,
Tensor self,
Scalar min) |
static Tensor |
torch.clamp_min_outf(Tensor self,
Scalar min,
Tensor out) |
static Tensor |
torch.clamp_min(Tensor self,
Scalar min) |
static Tensor |
torch.constant_(Tensor tensor,
Scalar value)
Fills the given tensor with the provided value in-place, and returns it.
|
static Tensor |
torch.constant_pad_nd_out(Tensor out,
Tensor self,
long[] pad,
Scalar value) |
static Tensor |
torch.constant_pad_nd_out(Tensor out,
Tensor self,
LongArrayRef pad,
Scalar value) |
static Tensor |
torch.constant_pad_nd_outf(Tensor self,
long[] pad,
Scalar value,
Tensor out) |
static Tensor |
torch.constant_pad_nd_outf(Tensor self,
LongArrayRef pad,
Scalar value,
Tensor out) |
static Tensor |
torch.constant_pad_nd_symint_out(Tensor out,
Tensor self,
SymIntArrayRef pad,
Scalar value) |
static Tensor |
torch.constant_pad_nd_symint_outf(Tensor self,
SymIntArrayRef pad,
Scalar value,
Tensor out) |
static Tensor |
torch.constant_pad_nd_symint(Tensor self,
SymIntArrayRef pad,
Scalar value) |
static Tensor |
torch.constant_pad_nd(Tensor self,
long[] pad,
Scalar value) |
static Tensor |
torch.constant_pad_nd(Tensor self,
LongArrayRef pad,
Scalar value) |
static Tensor |
torch.copysign_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.copysign_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.copysign(Tensor self,
Scalar other) |
static Tensor |
torch.cumulative_trapezoid(Tensor y,
Scalar dx,
long dim) |
static Tensor |
torch.dist_out(Tensor out,
Tensor self,
Tensor other,
Scalar p) |
static Tensor |
torch.dist_outf(Tensor self,
Tensor other,
Scalar p,
Tensor out) |
static Tensor |
torch.dist(Tensor self,
Tensor other,
Scalar p) |
static Tensor |
torch.div_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.div_out(Tensor out,
Tensor self,
Scalar other,
StringViewOptional rounding_mode) |
static Tensor |
torch.div_outf(Tensor self,
Scalar other,
StringViewOptional rounding_mode,
Tensor out) |
static Tensor |
torch.div_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.div(Tensor self,
Scalar other) |
static Tensor |
torch.div(Tensor self,
Scalar other,
StringViewOptional rounding_mode) |
static Tensor |
torch.divide(Scalar x,
Tensor y) |
static Tensor |
torch.divide(Tensor self,
Scalar other) |
static Tensor |
torch.divide(Tensor self,
Scalar other,
StringViewOptional rounding_mode) |
static Tensor |
torch.elu_(Tensor self,
Scalar alpha,
Scalar scale,
Scalar input_scale) |
static Tensor |
torch.elu_backward_out(Tensor grad_input,
Tensor grad_output,
Scalar alpha,
Scalar scale,
Scalar input_scale,
boolean is_result,
Tensor self_or_result) |
static Tensor |
torch.elu_backward_outf(Tensor grad_output,
Scalar alpha,
Scalar scale,
Scalar input_scale,
boolean is_result,
Tensor self_or_result,
Tensor grad_input) |
static Tensor |
torch.elu_backward(Tensor grad_output,
Scalar alpha,
Scalar scale,
Scalar input_scale,
boolean is_result,
Tensor self_or_result) |
static Tensor |
torch.elu_out(Tensor out,
Tensor self,
Scalar alpha,
Scalar scale,
Scalar input_scale) |
static Tensor |
torch.elu_outf(Tensor self,
Scalar alpha,
Scalar scale,
Scalar input_scale,
Tensor out) |
static Tensor |
torch.elu(Tensor self,
Scalar alpha,
Scalar scale,
Scalar input_scale) |
static Tensor |
torch.eq_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.eq_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.eq(Tensor self,
Scalar other) |
static Tensor |
torch.equals(Scalar x,
Tensor y) |
static Tensor |
torch.equals(Tensor x,
Scalar y) |
static Tensor |
torch.fbgemm_linear_int8_weight_fp32_activation(Tensor input,
Tensor weight,
Tensor packed,
Tensor col_offsets,
Scalar weight_scale,
Scalar weight_zero_point,
Tensor bias) |
static Tensor |
torch.fbgemm_linear_int8_weight(Tensor input,
Tensor weight,
Tensor packed,
Tensor col_offsets,
Scalar weight_scale,
Scalar weight_zero_point,
Tensor bias) |
static Tensor |
torch.fill_(Tensor self,
Scalar value) |
static Tensor |
torch.fill_out(Tensor out,
Tensor self,
Scalar value) |
static Tensor |
torch.fill_outf(Tensor self,
Scalar value,
Tensor out) |
static Tensor |
torch.float_power_out(Tensor out,
Scalar self,
Tensor exponent) |
static Tensor |
torch.float_power_out(Tensor out,
Tensor self,
Scalar exponent) |
static Tensor |
torch.float_power_outf(Scalar self,
Tensor exponent,
Tensor out) |
static Tensor |
torch.float_power_outf(Tensor self,
Scalar exponent,
Tensor out) |
static Tensor |
torch.float_power(Scalar self,
Tensor exponent) |
static Tensor |
torch.float_power(Tensor self,
Scalar exponent) |
static Tensor |
torch.floor_divide(Tensor self,
Scalar other) |
static Tensor |
torch.fmod_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.fmod_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.fmod(Tensor self,
Scalar other) |
static Tensor |
torch.full_like_out(Tensor out,
Tensor self,
Scalar fill_value) |
static Tensor |
torch.full_like_out(Tensor out,
Tensor self,
Scalar fill_value,
MemoryFormatOptional memory_format) |
static Tensor |
torch.full_like_outf(Tensor self,
Scalar fill_value,
MemoryFormatOptional memory_format,
Tensor out) |
static Tensor |
torch.full_like(Tensor self,
Scalar fill_value) |
static Tensor |
torch.full_like(Tensor self,
Scalar fill_value,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory,
MemoryFormatOptional memory_format) |
static Tensor |
torch.full_like(Tensor self,
Scalar fill_value,
TensorOptions options,
MemoryFormatOptional memory_format) |
static Tensor |
torch.full_out(Tensor out,
long[] size,
Scalar fill_value) |
static Tensor |
torch.full_out(Tensor out,
long[] size,
Scalar fill_value,
DimnameListOptional names) |
static Tensor |
torch.full_out(Tensor out,
LongArrayRef size,
Scalar fill_value) |
static Tensor |
torch.full_out(Tensor out,
LongArrayRef size,
Scalar fill_value,
DimnameListOptional names) |
static Tensor |
torch.full_outf(long[] size,
Scalar fill_value,
DimnameListOptional names,
Tensor out) |
static Tensor |
torch.full_outf(long[] size,
Scalar fill_value,
Tensor out) |
static Tensor |
torch.full_outf(LongArrayRef size,
Scalar fill_value,
DimnameListOptional names,
Tensor out) |
static Tensor |
torch.full_outf(LongArrayRef size,
Scalar fill_value,
Tensor out) |
static Tensor |
torch.full_symint_out(Tensor out,
SymIntArrayRef size,
Scalar fill_value) |
static Tensor |
torch.full_symint_outf(SymIntArrayRef size,
Scalar fill_value,
Tensor out) |
static Tensor |
torch.full_symint(SymIntArrayRef size,
Scalar fill_value) |
static Tensor |
torch.full_symint(SymIntArrayRef size,
Scalar fill_value,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.full_symint(SymIntArrayRef size,
Scalar fill_value,
TensorOptions options) |
static Tensor |
torch.full(long[] size,
Scalar fill_value) |
static Tensor |
torch.full(long[] size,
Scalar fill_value,
DimnameListOptional names) |
static Tensor |
torch.full(long[] size,
Scalar fill_value,
DimnameListOptional names,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.full(long[] size,
Scalar fill_value,
DimnameListOptional names,
TensorOptions options) |
static Tensor |
torch.full(long[] size,
Scalar fill_value,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.full(long[] size,
Scalar fill_value,
TensorOptions options) |
static Tensor |
torch.full(LongArrayRef size,
Scalar fill_value) |
static Tensor |
torch.full(LongArrayRef size,
Scalar fill_value,
DimnameListOptional names) |
static Tensor |
torch.full(LongArrayRef size,
Scalar fill_value,
DimnameListOptional names,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.full(LongArrayRef size,
Scalar fill_value,
DimnameListOptional names,
TensorOptions options) |
static Tensor |
torch.full(LongArrayRef size,
Scalar fill_value,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.full(LongArrayRef size,
Scalar fill_value,
TensorOptions options) |
static Tensor |
torch.ge_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.ge_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.ge(Tensor self,
Scalar other) |
static TensorVector |
torch.gradient(Tensor self,
Scalar spacing,
long... dim) |
static TensorVector |
torch.gradient(Tensor self,
Scalar spacing,
long[] dim,
long edge_order) |
static TensorVector |
torch.gradient(Tensor self,
Scalar spacing,
LongArrayRef dim) |
static TensorVector |
torch.gradient(Tensor self,
Scalar spacing,
LongArrayRef dim,
long edge_order) |
static Tensor |
torch.greater_equal_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.greater_equal_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.greater_equal(Tensor self,
Scalar other) |
static Tensor |
torch.greater_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.greater_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.greater(Tensor self,
Scalar other) |
static Tensor |
torch.greaterThan(Scalar x,
Tensor y) |
static Tensor |
torch.greaterThan(Tensor x,
Scalar y) |
static Tensor |
torch.greaterThanEquals(Scalar x,
Tensor y) |
static Tensor |
torch.greaterThanEquals(Tensor x,
Scalar y) |
static Tensor |
torch.gt_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.gt_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.gt(Tensor self,
Scalar other) |
static Tensor |
torch.hardshrink_backward_out(Tensor grad_input,
Tensor grad_out,
Tensor self,
Scalar lambd) |
static Tensor |
torch.hardshrink_backward_outf(Tensor grad_out,
Tensor self,
Scalar lambd,
Tensor grad_input) |
static Tensor |
torch.hardshrink_backward(Tensor grad_out,
Tensor self,
Scalar lambd) |
static Tensor |
torch.hardshrink_out(Tensor out,
Tensor self,
Scalar lambd) |
static Tensor |
torch.hardshrink_outf(Tensor self,
Scalar lambd,
Tensor out) |
static Tensor |
torch.hardshrink(Tensor self,
Scalar lambd) |
static Tensor |
torch.hardtanh_(Tensor self,
Scalar min_val,
Scalar max_val) |
static Tensor |
torch.hardtanh_backward_out(Tensor grad_input,
Tensor grad_output,
Tensor self,
Scalar min_val,
Scalar max_val) |
static Tensor |
torch.hardtanh_backward_outf(Tensor grad_output,
Tensor self,
Scalar min_val,
Scalar max_val,
Tensor grad_input) |
static Tensor |
torch.hardtanh_backward(Tensor grad_output,
Tensor self,
Scalar min_val,
Scalar max_val) |
static Tensor |
torch.hardtanh_out(Tensor out,
Tensor self,
Scalar min_val,
Scalar max_val) |
static Tensor |
torch.hardtanh_outf(Tensor self,
Scalar min_val,
Scalar max_val,
Tensor out) |
static Tensor |
torch.hardtanh(Tensor self,
Scalar min_val,
Scalar max_val) |
static Tensor |
torch.hermite_polynomial_h_out(Tensor output,
Scalar x,
Tensor n) |
static Tensor |
torch.hermite_polynomial_h_out(Tensor output,
Tensor x,
Scalar n) |
static Tensor |
torch.hermite_polynomial_h(Scalar x,
Tensor n) |
static Tensor |
torch.hermite_polynomial_h(Tensor x,
Scalar n) |
static Tensor |
torch.hermite_polynomial_he_out(Tensor output,
Scalar x,
Tensor n) |
static Tensor |
torch.hermite_polynomial_he_out(Tensor output,
Tensor x,
Scalar n) |
static Tensor |
torch.hermite_polynomial_he(Scalar x,
Tensor n) |
static Tensor |
torch.hermite_polynomial_he(Tensor x,
Scalar n) |
static Tensor |
torch.histc_out(Tensor out,
Tensor self,
long bins,
Scalar min,
Scalar max) |
static Tensor |
torch.histc_outf(Tensor self,
long bins,
Scalar min,
Scalar max,
Tensor out) |
static Tensor |
torch.histc(Tensor self,
long bins,
Scalar min,
Scalar max) |
static Tensor |
torch.index_add_out(Tensor out,
Tensor self,
long dim,
Tensor index,
Tensor source,
Scalar alpha) |
static Tensor |
torch.index_add_outf(Tensor self,
long dim,
Tensor index,
Tensor source,
Scalar alpha,
Tensor out) |
static Tensor |
torch.index_add(Tensor self,
Dimname dim,
Tensor index,
Tensor source,
Scalar alpha) |
static Tensor |
torch.index_add(Tensor self,
long dim,
Tensor index,
Tensor source,
Scalar alpha) |
static Tensor |
torch.index_fill_out(Tensor out,
Tensor self,
long dim,
Tensor index,
Scalar value) |
static Tensor |
torch.index_fill_outf(Tensor self,
long dim,
Tensor index,
Scalar value,
Tensor out) |
static Tensor |
torch.index_fill(Tensor self,
Dimname dim,
Tensor index,
Scalar value) |
static Tensor |
torch.index_fill(Tensor self,
long dim,
Tensor index,
Scalar value) |
static Tensor |
torch.isin_out(Tensor out,
Scalar element,
Tensor test_elements) |
static Tensor |
torch.isin_out(Tensor out,
Scalar element,
Tensor test_elements,
boolean assume_unique,
boolean invert) |
static Tensor |
torch.isin_out(Tensor out,
Tensor elements,
Scalar test_element) |
static Tensor |
torch.isin_out(Tensor out,
Tensor elements,
Scalar test_element,
boolean assume_unique,
boolean invert) |
static Tensor |
torch.isin_outf(Scalar element,
Tensor test_elements,
boolean assume_unique,
boolean invert,
Tensor out) |
static Tensor |
torch.isin_outf(Tensor elements,
Scalar test_element,
boolean assume_unique,
boolean invert,
Tensor out) |
static Tensor |
torch.isin(Scalar element,
Tensor test_elements) |
static Tensor |
torch.isin(Scalar element,
Tensor test_elements,
boolean assume_unique,
boolean invert) |
static Tensor |
torch.isin(Tensor elements,
Scalar test_element) |
static Tensor |
torch.isin(Tensor elements,
Scalar test_element,
boolean assume_unique,
boolean invert) |
static Tensor |
torch.laguerre_polynomial_l_out(Tensor output,
Scalar x,
Tensor n) |
static Tensor |
torch.laguerre_polynomial_l_out(Tensor output,
Tensor x,
Scalar n) |
static Tensor |
torch.laguerre_polynomial_l(Scalar x,
Tensor n) |
static Tensor |
torch.laguerre_polynomial_l(Tensor x,
Scalar n) |
static Tensor |
torch.le_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.le_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.le(Tensor self,
Scalar other) |
static Tensor |
torch.leaky_relu_(Tensor self,
Scalar negative_slope) |
static Tensor |
torch.leaky_relu_backward_out(Tensor grad_input,
Tensor grad_output,
Tensor self,
Scalar negative_slope,
boolean self_is_result) |
static Tensor |
torch.leaky_relu_backward_outf(Tensor grad_output,
Tensor self,
Scalar negative_slope,
boolean self_is_result,
Tensor grad_input) |
static Tensor |
torch.leaky_relu_backward(Tensor grad_output,
Tensor self,
Scalar negative_slope,
boolean self_is_result) |
static Tensor |
torch.leaky_relu_out(Tensor out,
Tensor self,
Scalar negative_slope) |
static Tensor |
torch.leaky_relu_outf(Tensor self,
Scalar negative_slope,
Tensor out) |
static Tensor |
torch.leaky_relu(Tensor self,
Scalar negative_slope) |
static Tensor |
torch.legendre_polynomial_p_out(Tensor output,
Scalar x,
Tensor n) |
static Tensor |
torch.legendre_polynomial_p_out(Tensor output,
Tensor x,
Scalar n) |
static Tensor |
torch.legendre_polynomial_p(Scalar x,
Tensor n) |
static Tensor |
torch.legendre_polynomial_p(Tensor x,
Scalar n) |
static Tensor |
torch.lerp_out(Tensor out,
Tensor self,
Tensor end,
Scalar weight) |
static Tensor |
torch.lerp_outf(Tensor self,
Tensor end,
Scalar weight,
Tensor out) |
static Tensor |
torch.lerp(Tensor self,
Tensor end,
Scalar weight) |
static Tensor |
torch.less_equal_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.less_equal_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.less_equal(Tensor self,
Scalar other) |
static Tensor |
torch.less_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.less_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.less(Tensor self,
Scalar other) |
static Tensor |
torch.lessThan(Scalar x,
Tensor y) |
static Tensor |
torch.lessThan(Tensor x,
Scalar y) |
static Tensor |
torch.lessThanEquals(Scalar x,
Tensor y) |
static Tensor |
torch.lessThanEquals(Tensor x,
Scalar y) |
static Tensor |
torch.linalg_matrix_norm_out(Tensor out,
Tensor self,
Scalar ord) |
static Tensor |
torch.linalg_matrix_norm_out(Tensor out,
Tensor self,
Scalar ord,
long[] dim,
boolean keepdim,
ScalarTypeOptional dtype) |
static Tensor |
torch.linalg_matrix_norm_out(Tensor out,
Tensor self,
Scalar ord,
LongArrayRef dim,
boolean keepdim,
ScalarTypeOptional dtype) |
static Tensor |
torch.linalg_matrix_norm_outf(Tensor self,
Scalar ord,
long[] dim,
boolean keepdim,
ScalarTypeOptional dtype,
Tensor out) |
static Tensor |
torch.linalg_matrix_norm_outf(Tensor self,
Scalar ord,
LongArrayRef dim,
boolean keepdim,
ScalarTypeOptional dtype,
Tensor out) |
static Tensor |
torch.linalg_matrix_norm(Tensor self,
Scalar ord) |
static Tensor |
torch.linalg_matrix_norm(Tensor self,
Scalar ord,
long[] dim,
boolean keepdim,
ScalarTypeOptional dtype) |
static Tensor |
torch.linalg_matrix_norm(Tensor self,
Scalar ord,
LongArrayRef dim,
boolean keepdim,
ScalarTypeOptional dtype) |
static Tensor |
torch.linalg_vector_norm_out(Tensor out,
Tensor self,
Scalar ord,
long[] dim,
boolean keepdim,
ScalarTypeOptional dtype) |
static Tensor |
torch.linalg_vector_norm_out(Tensor out,
Tensor self,
Scalar ord,
LongArrayRefOptional dim,
boolean keepdim,
ScalarTypeOptional dtype) |
static Tensor |
torch.linalg_vector_norm_outf(Tensor self,
Scalar ord,
long[] dim,
boolean keepdim,
ScalarTypeOptional dtype,
Tensor out) |
static Tensor |
torch.linalg_vector_norm_outf(Tensor self,
Scalar ord,
LongArrayRefOptional dim,
boolean keepdim,
ScalarTypeOptional dtype,
Tensor out) |
static Tensor |
torch.linalg_vector_norm(Tensor self,
Scalar ord,
long[] dim,
boolean keepdim,
ScalarTypeOptional dtype) |
static Tensor |
torch.linalg_vector_norm(Tensor self,
Scalar ord,
LongArrayRefOptional dim,
boolean keepdim,
ScalarTypeOptional dtype) |
static Tensor |
torch.linspace_out(Tensor out,
Scalar start,
Scalar end,
long steps) |
static Tensor |
torch.linspace_outf(Scalar start,
Scalar end,
long steps,
Tensor out) |
static Tensor |
torch.linspace(Scalar start,
Scalar end,
long steps) |
static Tensor |
torch.linspace(Scalar start,
Scalar end,
long steps,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.linspace(Scalar start,
Scalar end,
long steps,
TensorOptions options) |
static Tensor |
torch.logspace_out(Tensor out,
Scalar start,
Scalar end,
long steps) |
static Tensor |
torch.logspace_out(Tensor out,
Scalar start,
Scalar end,
long steps,
double base) |
static Tensor |
torch.logspace_outf(Scalar start,
Scalar end,
long steps,
double base,
Tensor out) |
static Tensor |
torch.logspace(Scalar start,
Scalar end,
long steps) |
static Tensor |
torch.logspace(Scalar start,
Scalar end,
long steps,
double base,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.logspace(Scalar start,
Scalar end,
long steps,
double base,
TensorOptions options) |
static Tensor |
torch.lt_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.lt_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.lt(Tensor self,
Scalar other) |
static Tensor |
torch.masked_fill_out(Tensor out,
Tensor self,
Tensor mask,
Scalar value) |
static Tensor |
torch.masked_fill_outf(Tensor self,
Tensor mask,
Scalar value,
Tensor out) |
static Tensor |
torch.masked_fill(Tensor self,
Tensor mask,
Scalar value) |
static Tensor |
torch.matrix_norm_out(Tensor self,
Scalar ord,
long[] dim,
boolean keepdim,
ScalarTypeOptional dtype,
Tensor result) |
static Tensor |
torch.matrix_norm_out(Tensor self,
Scalar ord,
LongArrayRef dim,
boolean keepdim,
ScalarTypeOptional dtype,
Tensor result) |
static Tensor |
torch.matrix_norm(Tensor self,
Scalar ord,
long[] dim,
boolean keepdim,
ScalarTypeOptional dtype) |
static Tensor |
torch.matrix_norm(Tensor self,
Scalar ord,
LongArrayRef dim,
boolean keepdim,
ScalarTypeOptional dtype) |
static Tensor |
torch.mod(Scalar x,
Tensor y) |
static Tensor |
torch.mod(Tensor x,
Scalar y) |
static Tensor |
torch.mul_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.mul_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.mul(Tensor self,
Scalar other) |
static Tensor |
torch.multi_margin_loss_backward_out(Tensor grad_input,
Tensor grad_output,
Tensor self,
Tensor target,
Scalar p,
Scalar margin) |
static Tensor |
torch.multi_margin_loss_backward_out(Tensor grad_input,
Tensor grad_output,
Tensor self,
Tensor target,
Scalar p,
Scalar margin,
TensorOptional weight,
long reduction) |
static Tensor |
torch.multi_margin_loss_backward_outf(Tensor grad_output,
Tensor self,
Tensor target,
Scalar p,
Scalar margin,
TensorOptional weight,
long reduction,
Tensor grad_input) |
static Tensor |
torch.multi_margin_loss_backward(Tensor grad_output,
Tensor self,
Tensor target,
Scalar p,
Scalar margin) |
static Tensor |
torch.multi_margin_loss_backward(Tensor grad_output,
Tensor self,
Tensor target,
Scalar p,
Scalar margin,
TensorOptional weight,
long reduction) |
static Tensor |
torch.multi_margin_loss_out(Tensor out,
Tensor self,
Tensor target,
Scalar p,
Scalar margin,
TensorOptional weight,
long reduction) |
static Tensor |
torch.multi_margin_loss_outf(Tensor self,
Tensor target,
Scalar p,
Scalar margin,
TensorOptional weight,
long reduction,
Tensor out) |
static Tensor |
torch.multi_margin_loss(Tensor self,
Tensor target,
Scalar p,
Scalar margin,
TensorOptional weight,
long reduction) |
static Tensor |
torch.multiply(Scalar x,
Tensor y) |
static Tensor |
torch.multiply(Tensor self,
Scalar other) |
static Tensor |
torch.native_norm_out(Tensor out,
Tensor self,
Scalar p) |
static Tensor |
torch.native_norm_outf(Tensor self,
Scalar p,
Tensor out) |
static Tensor |
torch.native_norm(Tensor self,
Scalar p) |
static Tensor |
torch.ne_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.ne_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.ne(Tensor self,
Scalar other) |
static Tensor |
torch.new_full_out(Tensor out,
Tensor self,
long[] size,
Scalar fill_value) |
static Tensor |
torch.new_full_out(Tensor out,
Tensor self,
LongArrayRef size,
Scalar fill_value) |
static Tensor |
torch.new_full_outf(Tensor self,
long[] size,
Scalar fill_value,
Tensor out) |
static Tensor |
torch.new_full_outf(Tensor self,
LongArrayRef size,
Scalar fill_value,
Tensor out) |
static Tensor |
torch.new_full_symint_out(Tensor out,
Tensor self,
SymIntArrayRef size,
Scalar fill_value) |
static Tensor |
torch.new_full_symint_outf(Tensor self,
SymIntArrayRef size,
Scalar fill_value,
Tensor out) |
static Tensor |
torch.norm_out(Tensor out,
Tensor self,
Scalar p) |
static Tensor |
torch.norm_outf(Tensor self,
Scalar p,
Tensor out) |
static Tensor |
torch.norm(Tensor self,
Scalar p) |
static Tensor |
torch.not_equal_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.not_equal_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.not_equal(Tensor self,
Scalar other) |
static Tensor |
torch.notEquals(Scalar x,
Tensor y) |
static Tensor |
torch.notEquals(Tensor x,
Scalar y) |
static Tensor |
torch.or(Scalar x,
Tensor y) |
static Tensor |
torch.or(Tensor x,
Scalar y) |
static Tensor |
torch.pow_out(Tensor out,
Scalar self,
Tensor exponent) |
static Tensor |
torch.pow_out(Tensor out,
Tensor self,
Scalar exponent) |
static Tensor |
torch.pow_outf(Scalar self,
Tensor exponent,
Tensor out) |
static Tensor |
torch.pow_outf(Tensor self,
Scalar exponent,
Tensor out) |
static Tensor |
torch.pow(Scalar self,
Tensor exponent) |
static Tensor |
torch.pow(Tensor self,
Scalar exponent) |
static Tensor |
torch.quantized_gru_cell(Tensor input,
Tensor hx,
Tensor w_ih,
Tensor w_hh,
Tensor b_ih,
Tensor b_hh,
Tensor packed_ih,
Tensor packed_hh,
Tensor col_offsets_ih,
Tensor col_offsets_hh,
Scalar scale_ih,
Scalar scale_hh,
Scalar zero_point_ih,
Scalar zero_point_hh) |
static T_TensorTensor_T |
torch.quantized_lstm_cell(Tensor input,
TensorArrayRef hx,
Tensor w_ih,
Tensor w_hh,
Tensor b_ih,
Tensor b_hh,
Tensor packed_ih,
Tensor packed_hh,
Tensor col_offsets_ih,
Tensor col_offsets_hh,
Scalar scale_ih,
Scalar scale_hh,
Scalar zero_point_ih,
Scalar zero_point_hh) |
static T_TensorTensor_T |
torch.quantized_lstm_cell(Tensor input,
TensorVector hx,
Tensor w_ih,
Tensor w_hh,
Tensor b_ih,
Tensor b_hh,
Tensor packed_ih,
Tensor packed_hh,
Tensor col_offsets_ih,
Tensor col_offsets_hh,
Scalar scale_ih,
Scalar scale_hh,
Scalar zero_point_ih,
Scalar zero_point_hh) |
static Tensor |
torch.quantized_rnn_relu_cell(Tensor input,
Tensor hx,
Tensor w_ih,
Tensor w_hh,
Tensor b_ih,
Tensor b_hh,
Tensor packed_ih,
Tensor packed_hh,
Tensor col_offsets_ih,
Tensor col_offsets_hh,
Scalar scale_ih,
Scalar scale_hh,
Scalar zero_point_ih,
Scalar zero_point_hh) |
static Tensor |
torch.quantized_rnn_tanh_cell(Tensor input,
Tensor hx,
Tensor w_ih,
Tensor w_hh,
Tensor b_ih,
Tensor b_hh,
Tensor packed_ih,
Tensor packed_hh,
Tensor col_offsets_ih,
Tensor col_offsets_hh,
Scalar scale_ih,
Scalar scale_hh,
Scalar zero_point_ih,
Scalar zero_point_hh) |
static Tensor |
torch.range_out(Tensor out,
Scalar start,
Scalar end) |
static Tensor |
torch.range_out(Tensor out,
Scalar start,
Scalar end,
Scalar step) |
static Tensor |
torch.range_outf(Scalar start,
Scalar end,
Scalar step,
Tensor out) |
static Tensor |
torch.range_outf(Scalar start,
Scalar end,
Tensor out) |
static Tensor |
torch.range(Scalar start,
Scalar end,
Scalar step,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.range(Scalar start,
Scalar end,
Scalar step,
TensorOptions options) |
static Tensor |
torch.range(Scalar start,
Scalar end,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.range(Scalar start,
Scalar end,
TensorOptions options) |
static Tensor |
torch.remainder_out(Tensor out,
Scalar self,
Tensor other) |
static Tensor |
torch.remainder_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.remainder_outf(Scalar self,
Tensor other,
Tensor out) |
static Tensor |
torch.remainder_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.remainder(Scalar self,
Tensor other) |
static Tensor |
torch.remainder(Tensor self,
Scalar other) |
static Tensor |
torch.renorm_out(Tensor out,
Tensor self,
Scalar p,
long dim,
Scalar maxnorm) |
static Tensor |
torch.renorm_outf(Tensor self,
Scalar p,
long dim,
Scalar maxnorm,
Tensor out) |
static Tensor |
torch.renorm(Tensor self,
Scalar p,
long dim,
Scalar maxnorm) |
static torch.ScalarType |
torch.result_type(Scalar scalar1,
Scalar scalar2) |
static torch.ScalarType |
torch.result_type(Scalar scalar,
Tensor tensor) |
static torch.ScalarType |
torch.result_type(Tensor tensor,
Scalar other) |
static Tensor |
torch.rrelu_(Tensor self,
Scalar lower,
Scalar upper,
boolean training,
GeneratorOptional generator) |
static Tensor |
torch.rrelu_with_noise_(Tensor self,
Tensor noise,
Scalar lower,
Scalar upper,
boolean training,
GeneratorOptional generator) |
static Tensor |
torch.rrelu_with_noise_backward_out(Tensor out,
Tensor grad_output,
Tensor self,
Tensor noise,
Scalar lower,
Scalar upper,
boolean training,
boolean self_is_result) |
static Tensor |
torch.rrelu_with_noise_backward_outf(Tensor grad_output,
Tensor self,
Tensor noise,
Scalar lower,
Scalar upper,
boolean training,
boolean self_is_result,
Tensor out) |
static Tensor |
torch.rrelu_with_noise_backward(Tensor grad_output,
Tensor self,
Tensor noise,
Scalar lower,
Scalar upper,
boolean training,
boolean self_is_result) |
static Tensor |
torch.rrelu_with_noise_out(Tensor out,
Tensor self,
Tensor noise,
Scalar lower,
Scalar upper,
boolean training,
GeneratorOptional generator) |
static Tensor |
torch.rrelu_with_noise_outf(Tensor self,
Tensor noise,
Scalar lower,
Scalar upper,
boolean training,
GeneratorOptional generator,
Tensor out) |
static Tensor |
torch.rrelu_with_noise(Tensor self,
Tensor noise,
Scalar lower,
Scalar upper,
boolean training,
GeneratorOptional generator) |
static Tensor |
torch.rrelu(Tensor self,
Scalar lower,
Scalar upper,
boolean training,
GeneratorOptional generator) |
static Tensor |
torch.rsub_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.rsub_out(Tensor out,
Tensor self,
Scalar other,
Scalar alpha) |
static Tensor |
torch.rsub_out(Tensor out,
Tensor self,
Tensor other,
Scalar alpha) |
static Tensor |
torch.rsub_outf(Tensor self,
Scalar other,
Scalar alpha,
Tensor out) |
static Tensor |
torch.rsub_outf(Tensor self,
Tensor other,
Scalar alpha,
Tensor out) |
static Tensor |
torch.rsub(Tensor self,
Scalar other) |
static Tensor |
torch.rsub(Tensor self,
Scalar other,
Scalar alpha) |
static Tensor |
torch.rsub(Tensor self,
Tensor other,
Scalar alpha) |
static Tensor |
torch.scalar_tensor_out(Tensor out,
Scalar s) |
static Tensor |
torch.scalar_tensor_outf(Scalar s,
Tensor out) |
static Tensor |
torch.scalar_tensor_static(Scalar s,
ScalarTypeOptional dtype_opt,
DeviceOptional device_opt) |
static Tensor |
torch.scalar_tensor(Scalar s) |
static Tensor |
torch.scalar_tensor(Scalar s,
ScalarTypeOptional dtype,
LayoutOptional layout,
DeviceOptional device,
BoolOptional pin_memory) |
static Tensor |
torch.scalar_tensor(Scalar s,
TensorOptions options) |
static Tensor |
torch.scalar_to_tensor(Scalar s) |
static Tensor |
torch.scalar_to_tensor(Scalar s,
Device device) |
static Tensor |
torch.scalarToTensor(Scalar v,
TensorOptions options,
Device self_device) |
static Tensor |
torch.scalarToTensorNonNativeDeviceType(Scalar v,
TensorOptions options) |
static Tensor |
torch.scatter_out(Tensor out,
Tensor self,
long dim,
Tensor index,
Scalar value) |
static Tensor |
torch.scatter_out(Tensor out,
Tensor self,
long dim,
Tensor index,
Scalar value,
BytePointer reduce) |
static Tensor |
torch.scatter_out(Tensor out,
Tensor self,
long dim,
Tensor index,
Scalar value,
String reduce) |
static Tensor |
torch.scatter_outf(Tensor self,
long dim,
Tensor index,
Scalar value,
BytePointer reduce,
Tensor out) |
static Tensor |
torch.scatter_outf(Tensor self,
long dim,
Tensor index,
Scalar value,
String reduce,
Tensor out) |
static Tensor |
torch.scatter_outf(Tensor self,
long dim,
Tensor index,
Scalar value,
Tensor out) |
static Tensor |
torch.scatter(Tensor self,
Dimname dim,
Tensor index,
Scalar value) |
static Tensor |
torch.scatter(Tensor self,
long dim,
Tensor index,
Scalar value) |
static Tensor |
torch.scatter(Tensor self,
long dim,
Tensor index,
Scalar value,
BytePointer reduce) |
static Tensor |
torch.scatter(Tensor self,
long dim,
Tensor index,
Scalar value,
String reduce) |
static Tensor |
torch.searchsorted_out(Tensor out,
Tensor sorted_sequence,
Scalar self) |
static Tensor |
torch.searchsorted_out(Tensor out,
Tensor sorted_sequence,
Scalar self,
boolean out_int32,
boolean right,
StringViewOptional side,
TensorOptional sorter) |
static Tensor |
torch.searchsorted_outf(Tensor sorted_sequence,
Scalar self,
boolean out_int32,
boolean right,
StringViewOptional side,
TensorOptional sorter,
Tensor out) |
static Tensor |
torch.searchsorted(Tensor sorted_sequence,
Scalar self) |
static Tensor |
torch.searchsorted(Tensor sorted_sequence,
Scalar self,
boolean out_int32,
boolean right,
StringViewOptional side,
TensorOptional sorter) |
static Tensor |
torch.shifted_chebyshev_polynomial_t_out(Tensor output,
Scalar x,
Tensor n) |
static Tensor |
torch.shifted_chebyshev_polynomial_t_out(Tensor output,
Tensor x,
Scalar n) |
static Tensor |
torch.shifted_chebyshev_polynomial_t(Scalar x,
Tensor n) |
static Tensor |
torch.shifted_chebyshev_polynomial_t(Tensor x,
Scalar n) |
static Tensor |
torch.shifted_chebyshev_polynomial_u_out(Tensor output,
Scalar x,
Tensor n) |
static Tensor |
torch.shifted_chebyshev_polynomial_u_out(Tensor output,
Tensor x,
Scalar n) |
static Tensor |
torch.shifted_chebyshev_polynomial_u(Scalar x,
Tensor n) |
static Tensor |
torch.shifted_chebyshev_polynomial_u(Tensor x,
Scalar n) |
static Tensor |
torch.shifted_chebyshev_polynomial_v_out(Tensor output,
Scalar x,
Tensor n) |
static Tensor |
torch.shifted_chebyshev_polynomial_v_out(Tensor output,
Tensor x,
Scalar n) |
static Tensor |
torch.shifted_chebyshev_polynomial_v(Scalar x,
Tensor n) |
static Tensor |
torch.shifted_chebyshev_polynomial_v(Tensor x,
Scalar n) |
static Tensor |
torch.shifted_chebyshev_polynomial_w_out(Tensor output,
Scalar x,
Tensor n) |
static Tensor |
torch.shifted_chebyshev_polynomial_w_out(Tensor output,
Tensor x,
Scalar n) |
static Tensor |
torch.shifted_chebyshev_polynomial_w(Scalar x,
Tensor n) |
static Tensor |
torch.shifted_chebyshev_polynomial_w(Tensor x,
Scalar n) |
static Pointer |
torch.shiftLeft(Pointer out,
Scalar s) |
static Tensor |
torch.softplus_backward_out(Tensor grad_input,
Tensor grad_output,
Tensor self,
Scalar beta,
Scalar threshold) |
static Tensor |
torch.softplus_backward_outf(Tensor grad_output,
Tensor self,
Scalar beta,
Scalar threshold,
Tensor grad_input) |
static Tensor |
torch.softplus_backward(Tensor grad_output,
Tensor self,
Scalar beta,
Scalar threshold) |
static Tensor |
torch.softplus_out(Tensor out,
Tensor self,
Scalar beta,
Scalar threshold) |
static Tensor |
torch.softplus_outf(Tensor self,
Scalar beta,
Scalar threshold,
Tensor out) |
static Tensor |
torch.softplus(Tensor self,
Scalar beta,
Scalar threshold) |
static Tensor |
torch.softshrink_backward_out(Tensor grad_input,
Tensor grad_output,
Tensor self,
Scalar lambd) |
static Tensor |
torch.softshrink_backward_outf(Tensor grad_output,
Tensor self,
Scalar lambd,
Tensor grad_input) |
static Tensor |
torch.softshrink_backward(Tensor grad_output,
Tensor self,
Scalar lambd) |
static Tensor |
torch.softshrink_out(Tensor out,
Tensor self,
Scalar lambd) |
static Tensor |
torch.softshrink_outf(Tensor self,
Scalar lambd,
Tensor out) |
static Tensor |
torch.softshrink(Tensor self,
Scalar lambd) |
static Tensor |
torch.sparse_sampled_addmm_out(Tensor out,
Tensor self,
Tensor mat1,
Tensor mat2,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.sparse_sampled_addmm_outf(Tensor self,
Tensor mat1,
Tensor mat2,
Scalar beta,
Scalar alpha,
Tensor out) |
static Tensor |
torch.sparse_sampled_addmm(Tensor self,
Tensor mat1,
Tensor mat2,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.special_chebyshev_polynomial_t_out(Tensor out,
Scalar x,
Tensor n) |
static Tensor |
torch.special_chebyshev_polynomial_t_out(Tensor out,
Tensor x,
Scalar n) |
static Tensor |
torch.special_chebyshev_polynomial_t_outf(Scalar x,
Tensor n,
Tensor out) |
static Tensor |
torch.special_chebyshev_polynomial_t_outf(Tensor x,
Scalar n,
Tensor out) |
static Tensor |
torch.special_chebyshev_polynomial_t(Scalar x,
Tensor n) |
static Tensor |
torch.special_chebyshev_polynomial_t(Tensor x,
Scalar n) |
static Tensor |
torch.special_chebyshev_polynomial_u_out(Tensor out,
Scalar x,
Tensor n) |
static Tensor |
torch.special_chebyshev_polynomial_u_out(Tensor out,
Tensor x,
Scalar n) |
static Tensor |
torch.special_chebyshev_polynomial_u_outf(Scalar x,
Tensor n,
Tensor out) |
static Tensor |
torch.special_chebyshev_polynomial_u_outf(Tensor x,
Scalar n,
Tensor out) |
static Tensor |
torch.special_chebyshev_polynomial_u(Scalar x,
Tensor n) |
static Tensor |
torch.special_chebyshev_polynomial_u(Tensor x,
Scalar n) |
static Tensor |
torch.special_chebyshev_polynomial_v_out(Tensor out,
Scalar x,
Tensor n) |
static Tensor |
torch.special_chebyshev_polynomial_v_out(Tensor out,
Tensor x,
Scalar n) |
static Tensor |
torch.special_chebyshev_polynomial_v_outf(Scalar x,
Tensor n,
Tensor out) |
static Tensor |
torch.special_chebyshev_polynomial_v_outf(Tensor x,
Scalar n,
Tensor out) |
static Tensor |
torch.special_chebyshev_polynomial_v(Scalar x,
Tensor n) |
static Tensor |
torch.special_chebyshev_polynomial_v(Tensor x,
Scalar n) |
static Tensor |
torch.special_chebyshev_polynomial_w_out(Tensor out,
Scalar x,
Tensor n) |
static Tensor |
torch.special_chebyshev_polynomial_w_out(Tensor out,
Tensor x,
Scalar n) |
static Tensor |
torch.special_chebyshev_polynomial_w_outf(Scalar x,
Tensor n,
Tensor out) |
static Tensor |
torch.special_chebyshev_polynomial_w_outf(Tensor x,
Scalar n,
Tensor out) |
static Tensor |
torch.special_chebyshev_polynomial_w(Scalar x,
Tensor n) |
static Tensor |
torch.special_chebyshev_polynomial_w(Tensor x,
Scalar n) |
static Tensor |
torch.special_hermite_polynomial_h_out(Tensor out,
Scalar x,
Tensor n) |
static Tensor |
torch.special_hermite_polynomial_h_out(Tensor out,
Tensor x,
Scalar n) |
static Tensor |
torch.special_hermite_polynomial_h_outf(Scalar x,
Tensor n,
Tensor out) |
static Tensor |
torch.special_hermite_polynomial_h_outf(Tensor x,
Scalar n,
Tensor out) |
static Tensor |
torch.special_hermite_polynomial_h(Scalar x,
Tensor n) |
static Tensor |
torch.special_hermite_polynomial_h(Tensor x,
Scalar n) |
static Tensor |
torch.special_hermite_polynomial_he_out(Tensor out,
Scalar x,
Tensor n) |
static Tensor |
torch.special_hermite_polynomial_he_out(Tensor out,
Tensor x,
Scalar n) |
static Tensor |
torch.special_hermite_polynomial_he_outf(Scalar x,
Tensor n,
Tensor out) |
static Tensor |
torch.special_hermite_polynomial_he_outf(Tensor x,
Scalar n,
Tensor out) |
static Tensor |
torch.special_hermite_polynomial_he(Scalar x,
Tensor n) |
static Tensor |
torch.special_hermite_polynomial_he(Tensor x,
Scalar n) |
static Tensor |
torch.special_laguerre_polynomial_l_out(Tensor out,
Scalar x,
Tensor n) |
static Tensor |
torch.special_laguerre_polynomial_l_out(Tensor out,
Tensor x,
Scalar n) |
static Tensor |
torch.special_laguerre_polynomial_l_outf(Scalar x,
Tensor n,
Tensor out) |
static Tensor |
torch.special_laguerre_polynomial_l_outf(Tensor x,
Scalar n,
Tensor out) |
static Tensor |
torch.special_laguerre_polynomial_l(Scalar x,
Tensor n) |
static Tensor |
torch.special_laguerre_polynomial_l(Tensor x,
Scalar n) |
static Tensor |
torch.special_legendre_polynomial_p_out(Tensor out,
Scalar x,
Tensor n) |
static Tensor |
torch.special_legendre_polynomial_p_out(Tensor out,
Tensor x,
Scalar n) |
static Tensor |
torch.special_legendre_polynomial_p_outf(Scalar x,
Tensor n,
Tensor out) |
static Tensor |
torch.special_legendre_polynomial_p_outf(Tensor x,
Scalar n,
Tensor out) |
static Tensor |
torch.special_legendre_polynomial_p(Scalar x,
Tensor n) |
static Tensor |
torch.special_legendre_polynomial_p(Tensor x,
Scalar n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_t_out(Tensor out,
Scalar x,
Tensor n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_t_out(Tensor out,
Tensor x,
Scalar n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_t_outf(Scalar x,
Tensor n,
Tensor out) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_t_outf(Tensor x,
Scalar n,
Tensor out) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_t(Scalar x,
Tensor n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_t(Tensor x,
Scalar n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_u_out(Tensor out,
Scalar x,
Tensor n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_u_out(Tensor out,
Tensor x,
Scalar n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_u_outf(Scalar x,
Tensor n,
Tensor out) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_u_outf(Tensor x,
Scalar n,
Tensor out) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_u(Scalar x,
Tensor n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_u(Tensor x,
Scalar n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_v_out(Tensor out,
Scalar x,
Tensor n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_v_out(Tensor out,
Tensor x,
Scalar n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_v_outf(Scalar x,
Tensor n,
Tensor out) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_v_outf(Tensor x,
Scalar n,
Tensor out) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_v(Scalar x,
Tensor n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_v(Tensor x,
Scalar n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_w_out(Tensor out,
Scalar x,
Tensor n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_w_out(Tensor out,
Tensor x,
Scalar n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_w_outf(Scalar x,
Tensor n,
Tensor out) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_w_outf(Tensor x,
Scalar n,
Tensor out) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_w(Scalar x,
Tensor n) |
static Tensor |
torch.special_shifted_chebyshev_polynomial_w(Tensor x,
Scalar n) |
static Tensor |
torch.special_xlog1py_out(Tensor out,
Scalar self,
Tensor other) |
static Tensor |
torch.special_xlog1py_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.special_xlog1py_outf(Scalar self,
Tensor other,
Tensor out) |
static Tensor |
torch.special_xlog1py_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.special_xlog1py(Scalar self,
Tensor other) |
static Tensor |
torch.special_xlog1py(Tensor self,
Scalar other) |
static Tensor |
torch.special_xlogy_out(Tensor out,
Scalar self,
Tensor other) |
static Tensor |
torch.special_xlogy_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.special_xlogy_outf(Scalar self,
Tensor other,
Tensor out) |
static Tensor |
torch.special_xlogy_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.special_xlogy(Scalar self,
Tensor other) |
static Tensor |
torch.special_xlogy(Tensor self,
Scalar other) |
static Tensor |
torch.special_zeta_out(Tensor out,
Scalar self,
Tensor other) |
static Tensor |
torch.special_zeta_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.special_zeta_outf(Scalar self,
Tensor other,
Tensor out) |
static Tensor |
torch.special_zeta_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.special_zeta(Scalar self,
Tensor other) |
static Tensor |
torch.special_zeta(Tensor self,
Scalar other) |
static Tensor |
torch.sspaddmm_out(Tensor out,
Tensor self,
Tensor mat1,
Tensor mat2,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.sspaddmm_outf(Tensor self,
Tensor mat1,
Tensor mat2,
Scalar beta,
Scalar alpha,
Tensor out) |
static Tensor |
torch.sspaddmm(Tensor self,
Tensor mat1,
Tensor mat2,
Scalar beta,
Scalar alpha) |
static Tensor |
torch.sub_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.sub_out(Tensor out,
Tensor self,
Scalar other,
Scalar alpha) |
static Tensor |
torch.sub_out(Tensor out,
Tensor self,
Tensor other,
Scalar alpha) |
static Tensor |
torch.sub_outf(Tensor self,
Scalar other,
Scalar alpha,
Tensor out) |
static Tensor |
torch.sub_outf(Tensor self,
Tensor other,
Scalar alpha,
Tensor out) |
static Tensor |
torch.sub(Tensor self,
Scalar other) |
static Tensor |
torch.sub(Tensor self,
Scalar other,
Scalar alpha) |
static Tensor |
torch.sub(Tensor self,
Tensor other,
Scalar alpha) |
static Tensor |
torch.subtract_out(Tensor out,
Tensor self,
Tensor other,
Scalar alpha) |
static Tensor |
torch.subtract_outf(Tensor self,
Tensor other,
Scalar alpha,
Tensor out) |
static Tensor |
torch.subtract(Scalar x,
Tensor y) |
static Tensor |
torch.subtract(Tensor self,
Scalar other) |
static Tensor |
torch.subtract(Tensor self,
Scalar other,
Scalar alpha) |
static Tensor |
torch.subtract(Tensor self,
Tensor other,
Scalar alpha) |
static void |
torch.sym_constrain_range_for_size(Scalar size,
LongOptional min,
LongOptional max) |
static void |
torch.sym_constrain_range(Scalar size) |
static void |
torch.sym_constrain_range(Scalar size,
LongOptional min,
LongOptional max) |
static Tensor |
torch.threshold_(Tensor self,
Scalar threshold,
Scalar value) |
static Tensor |
torch.threshold_backward_out(Tensor grad_input,
Tensor grad_output,
Tensor self,
Scalar threshold) |
static Tensor |
torch.threshold_backward_outf(Tensor grad_output,
Tensor self,
Scalar threshold,
Tensor grad_input) |
static Tensor |
torch.threshold_backward(Tensor grad_output,
Tensor self,
Scalar threshold) |
static Tensor |
torch.threshold_out(Tensor out,
Tensor self,
Scalar threshold,
Scalar value) |
static Tensor |
torch.threshold_outf(Tensor self,
Scalar threshold,
Scalar value,
Tensor out) |
static Tensor |
torch.threshold(Tensor self,
Scalar threshold,
Scalar value) |
static Tensor |
torch.torch_arange(Scalar end) |
static Tensor |
torch.torch_arange(Scalar start,
Scalar end) |
static Tensor |
torch.torch_arange(Scalar start,
Scalar end,
Scalar step) |
static Tensor |
torch.torch_arange(Scalar start,
Scalar end,
Scalar step,
TensorOptions options) |
static Tensor |
torch.torch_arange(Scalar start,
Scalar end,
TensorOptions options) |
static Tensor |
torch.torch_arange(Scalar end,
TensorOptions options) |
static Tensor |
torch.torch_full_like(Tensor self,
Scalar fill_value) |
static Tensor |
torch.torch_full_like(Tensor self,
Scalar fill_value,
TensorOptions options,
MemoryFormatOptional memory_format) |
static Tensor |
torch.torch_full(long[] size,
Scalar fill_value) |
static Tensor |
torch.torch_full(long[] size,
Scalar fill_value,
DimnameListOptional names) |
static Tensor |
torch.torch_full(long[] size,
Scalar fill_value,
DimnameListOptional names,
TensorOptions options) |
static Tensor |
torch.torch_full(long[] size,
Scalar fill_value,
TensorOptions options) |
static Tensor |
torch.torch_full(LongArrayRef size,
Scalar fill_value) |
static Tensor |
torch.torch_full(LongArrayRef size,
Scalar fill_value,
DimnameListOptional names) |
static Tensor |
torch.torch_full(LongArrayRef size,
Scalar fill_value,
DimnameListOptional names,
TensorOptions options) |
static Tensor |
torch.torch_full(LongArrayRef size,
Scalar fill_value,
TensorOptions options) |
static Tensor |
torch.torch_linspace(Scalar start,
Scalar end,
long steps) |
static Tensor |
torch.torch_linspace(Scalar start,
Scalar end,
long steps,
TensorOptions options) |
static Tensor |
torch.torch_logspace(Scalar start,
Scalar end,
long steps) |
static Tensor |
torch.torch_logspace(Scalar start,
Scalar end,
long steps,
double base,
TensorOptions options) |
static Tensor |
torch.torch_range(Scalar start,
Scalar end,
Scalar step,
TensorOptions options) |
static Tensor |
torch.torch_range(Scalar start,
Scalar end,
TensorOptions options) |
static Tensor |
torch.torch_scalar_tensor(Scalar s) |
static Tensor |
torch.torch_scalar_tensor(Scalar s,
TensorOptions options) |
static BytePointer |
torch.toString(Scalar s) |
static Tensor |
torch.trapezoid(Tensor y,
Scalar dx,
long dim) |
static Tensor |
torch.true_divide(Tensor self,
Scalar other) |
static Tensor |
torch.vector_norm_out(Tensor result,
Tensor self,
Scalar ord,
long[] opt_dim,
boolean keepdim,
ScalarTypeOptional opt_dtype) |
static Tensor |
torch.vector_norm_out(Tensor result,
Tensor self,
Scalar ord,
LongArrayRefOptional opt_dim,
boolean keepdim,
ScalarTypeOptional opt_dtype) |
static Tensor |
torch.vector_norm(Tensor self,
Scalar ord,
long[] opt_dim,
boolean keepdim,
ScalarTypeOptional opt_dtype) |
static Tensor |
torch.vector_norm(Tensor self,
Scalar ord,
LongArrayRefOptional opt_dim,
boolean keepdim,
ScalarTypeOptional opt_dtype) |
static Tensor |
torch.where(Tensor condition,
Scalar self,
Scalar other) |
static Tensor |
torch.where(Tensor condition,
Scalar self,
Tensor other) |
static Tensor |
torch.where(Tensor condition,
Tensor self,
Scalar other) |
static Tensor |
torch.wrapped_scalar_tensor(Scalar scalar) |
static Tensor |
torch.wrapped_scalar_tensor(Scalar scalar,
Device device) |
static Tensor |
torch.xlog1py_out(Tensor result,
Scalar self,
Tensor other) |
static Tensor |
torch.xlog1py_out(Tensor result,
Tensor self,
Scalar other) |
static Tensor |
torch.xlog1py(Scalar self,
Tensor other) |
static Tensor |
torch.xlog1py(Tensor self,
Scalar other) |
static Tensor |
torch.xlogy_(Tensor self,
Scalar other) |
static Tensor |
torch.xlogy_out(Tensor out,
Scalar self,
Tensor other) |
static Tensor |
torch.xlogy_out(Tensor out,
Tensor self,
Scalar other) |
static Tensor |
torch.xlogy_outf(Scalar self,
Tensor other,
Tensor out) |
static Tensor |
torch.xlogy_outf(Tensor self,
Scalar other,
Tensor out) |
static Tensor |
torch.xlogy(Scalar self,
Tensor other) |
static Tensor |
torch.xlogy(Tensor self,
Scalar other) |
static Tensor |
torch.xor(Scalar x,
Tensor y) |
static Tensor |
torch.xor(Tensor x,
Scalar y) |
static Tensor |
torch.zeta_out(Tensor result,
Scalar self,
Tensor other) |
static Tensor |
torch.zeta_out(Tensor result,
Tensor self,
Scalar other) |
static Tensor |
torch.zeta(Scalar self,
Tensor other) |
static Tensor |
torch.zeta(Tensor self,
Scalar other) |