사용 가능한 TensorFlow 작업

이 페이지에는 Cloud TPU에서 사용 가능한 텐서플로우 Python API 및 그래프 연산자 목록이 수록되어 있습니다.

사용 가능한 Python API

아래 목록은 사용 가능한 TensorFlow Python API 집합에 대한 가이드입니다. 이 목록은 일부일 뿐 모든 내용을 포함하지는 않습니다. 사용 가능한 기본 요소로 구성되어 있는 경우 이 목록에 없는 라이브러리 함수도 사용 가능할 수 있습니다.

특정 연산자에 관한 권장사항은 성능 가이드를 참조하세요.

모듈 사용 가능한 Python API 댓글
tf tf.abs
tf.acosh
tf.add
tf.add_n
tf.angle
tf.arg_max dimension 인수는 컴파일-시간 상수여야 합니다.
tf.arg_min dimension 인수는 컴파일-시간 상수여야 합니다.
tf.asinh
tf.assign 리소스 변수로만 사용 가능합니다.
tf.assign_add 리소스 변수로만 사용 가능합니다.
tf.assign_sub 리소스 변수로만 사용 가능합니다.
tf.atan
tf.atan2
tf.atanh
tf.batch_to_space crops, block_shape 인수는 컴파일-시간 상수여야 합니다.
tf.batch_to_space_nd crops 인수는 컴파일-시간 상수여야 합니다.
tf.broadcast_dynamic_shape
tf.broadcast_static_shape
tf.case 시험용입니다(제어-흐름). 아직 안정적으로 작동하지 않을 수 있습니다.
tf.cast
tf.ceil
tf.cholesky 시험용입니다. 숫자 정밀도에 문제가 있을 수 있습니다.
tf.cholesky_solve 시험용입니다. 숫자 정밀도에 문제가 있을 수 있습니다.
tf.clip_by_average_norm
tf.clip_by_global_norm
tf.clip_by_norm
tf.clip_by_value
tf.complex
tf.concat concat_dim은 컴파일-시간 상수여야 합니다.
tf.cond 시험용입니다(제어-흐름). 아직 안정적으로 작동하지 않을 수 있습니다.
tf.conj
tf.constant
tf.convert_to_tensor
tf.cos
tf.cosh
tf.cross
tf.cumprod axis는 컴파일-시간 상수여야 합니다.
tf.cumsum axis는 컴파일-시간 상수여야 합니다.
tf.depth_to_space
tf.diag
tf.diag_part
tf.div int32 분할 속도가 다른 유형보다 느립니다.
tf.divide int32 분할 속도가 다른 유형보다 느립니다.
tf.dynamic_stitch indices는 컴파일-시간 상수여야 합니다.
tf.einsum
tf.equal
tf.erf
tf.erfc
tf.exp
tf.expand_dims dims는 컴파일-시간 상수여야 합니다.
tf.expm1
tf.extract_image_patches
tf.eye
tf.fake_quant_with_min_max_args
tf.fake_quant_with_min_max_args_gradient
tf.fake_quant_with_min_max_vars
tf.fake_quant_with_min_max_vars_gradient
tf.fft 시험용입니다.
tf.fft2d 시험용입니다.
tf.fft3d 시험용입니다.
tf.fill dims 인수는 컴파일-시간 상수여야 합니다.
tf.floor
tf.floordiv
tf.floormod
tf.foldl 시험용입니다(제어-흐름).
tf.foldr 시험용입니다(제어-흐름).
tf.gather axis는 컴파일-시간 상수여야 합니다.
tf.gather_nd
tf.greater
tf.greater_equal
tf.hessians 시험용입니다(제어-흐름).
tf.identity
tf.identity_n
tf.ifft 시험용입니다.
tf.ifft2d 시험용입니다.
tf.ifft3d 시험용입니다.
tf.imag
tf.invert_permutation x 인수는 컴파일-시간 상수여야 합니다.
tf.is_finite
tf.is_inf
tf.is_nan
tf.is_non_decreasing
tf.is_strictly_increasing
tf.less
tf.less_equal
tf.linspace start, stop, num 인수는 컴파일-시간 상수여야 합니다.
tf.log
tf.log1p
tf.log_sigmoid
tf.logical_and
tf.logical_or
tf.logical_not
tf.logical_xor
tf.matmul float32 누적값으로 bfloat16 matmul을 사용하세요.
tf.matrix_band_part
tf.matrix_diag
tf.matrix_diag_part
tf.matrix_set_diag
tf.matrix_triangular_solve 시험용입니다. 숫자 정밀도에 문제가 있을 수 있습니다.
tf.maximum
tf.meshgrid
tf.minimum
tf.mod
tf.multinomial num_samples 인수는 컴파일-시간 상수여야 합니다.
tf.multiply
tf.negative
tf.no_op
tf.norm
tf.not_equal
tf.one_hot depth는 컴파일-시간 상수여야 합니다.
tf.ones
tf.ones_like
tf.pad paddings 인수는 컴파일-시간 상수여야 합니다. REFLECT 패딩 기울기는 아직 사용할 수 없습니다.
tf.pow
tf.random_normal shape는 컴파일-시간 상수여야 합니다.
tf.random_uniform shape는 컴파일-시간 상수여야 합니다.
tf.range start, limit, delta 인수는 컴파일-시간 상수여야 합니다.
tf.rank
tf.real
tf.realdiv
tf.reciprocal
tf.reduce_all axis는 컴파일-시간 상수여야 합니다.
tf.reduce_any axis는 컴파일-시간 상수여야 합니다.
tf.reduce_logsumexp
tf.reduce_max axis는 컴파일-시간 상수여야 합니다.
tf.reduce_min axis는 컴파일-시간 상수여야 합니다.
tf.reduce_prod axis는 컴파일-시간 상수여야 합니다.
tf.reduce_sum axis는 컴파일-시간 상수여야 합니다.
tf.reshape shape 인수는 컴파일-시간 상수여야 합니다.
tf.reverse dims 인수는 컴파일-시간 상수여야 합니다.
tf.reverse_sequence
tf.reverse_v2 axis 인수는 컴파일-시간 상수여야 합니다.
tf.rint
tf.round
tf.rsqrt
tf.saturate_cast
tf.scalar_mul
tf.scan 시험용입니다(제어-흐름).
tf.scatter_nd
tf.sequence_mask
tf.shape
tf.shape_n
tf.sigmoid
tf.sign
tf.sin
tf.sinh
tf.size
tf.slice size는 컴파일-시간 상수여야 합니다. 또한 begin은 컴파일-시간 상수이거나 size는 음수가 아니어야 합니다. 역전파는 beginsize가 컴파일-시간 상수인 경우에만 지원됩니다.
tf.space_to_batch paddings, block_shape는 컴파일-시간 상수여야 합니다.
tf.space_to_batch_nd paddings는 컴파일-시간 상수여야 합니다.
tf.space_to_depth
tf.split axis는 컴파일-시간 상수여야 합니다.
tf.sqrt
tf.square
tf.squared_difference
tf.squeeze
tf.stack
tf.stop_gradient
tf.strided_slice
tf.tan
tf.tanh
tf.tensordot
tf.tile multiples 인수는 컴파일-시간 상수여야 합니다.
tf.to_bfloat16
tf.to_float
tf.to_int32
tf.to_int64 int64 지원은 제한됩니다.
tf.trace
tf.transpose perm 인수는 컴파일-시간 상수여야 합니다.
tf.truediv
tf.truncated_normal shape는 컴파일-시간 상수여야 합니다.
tf.truncatediv
tf.truncatemod
tf.unsorted_segment_sum
tf.unstack
tf.where xy가 모두 None이 아니어야 합니다. xy가 모두 None이 아닌 경우 연산자가 정적 형태를 갖지 않게 됩니다.
tf.while_loop while 루프의 기울기를 계산하려면 maximum_iterations 인수가 전달되어야 합니다.
tf.zeros
tf.zeros_like
tf.Tensor.__getitem__ 슬라이스의 시작, 끝, 진행 속도는 컴파일-시간 상수여야 합니다.
tf.bitwise tf.bitwise_and
tf.bitwise_or
tf.bitwise_invert
tf.contrib.stateless tf.contrib.stateless.stateless_random_normal
tf.contrib.stateless.stateless_random_uniform
tf.image tf.image.adjust_brightness
tf.image.adjust_contrast
tf.image.adjust_gamma
tf.image.adjust_hue
tf.image.adjust_saturation
tf.image.central_crop Crop 계수는 컴파일-시간 상수여야 합니다.
tf.image.convert_image_dtype
tf.image.flip_left_right
tf.image.flip_up_down
tf.image.grayscale_to_rgb
tf.image.hsv_to_rgb
tf.image.resize_bilinear align_corners=True만 사용할 수 있습니다. size는 컴파일-시간 상수여야 합니다.
tf.image.random_brightness
tf.image.random_contrast
tf.image.random_flip_left_right
tf.image.random_flip_up_down
tf.image.random_hue
tf.image.random_saturation
tf.image.rgb_to_hsv
tf.image.rgb_to_grayscale
tf.image.rot90
tf.image.total_variation
tf.image.transpose_image
tf.layers tf.layers.average_pooling1d
tf.layers.average_pooling2d
tf.layers.average_pooling1d
tf.layers.batch_normalization
tf.layers.conv1d
tf.layers.conv2d
tf.layers.conv2d_transpose
tf.layers.conv3d
tf.layers.conv3d_transpose
tf.layers.dense
tf.layers.dropout
tf.layers.flatten
tf.layers.max_pooling1d
tf.layers.max_pooling2d
tf.layers.max_pooling3d
tf.layers.separable_conv2d
tf.nn tf.nn.atrous_conv2d
tf.nn.atrous_conv2d_transpose
tf.nn.avg_pool
tf.nn.avg_pool3d
tf.nn.batch_normalization
tf.nn.bias_add
tf.nn.conv1d
tf.nn.conv2d
tf.nn.conv2d_backprop_filter
tf.nn.conv2d_backprop_input
tf.nn.conv2d_transpose
tf.nn.conv3d
tf.nn.conv3d_backprop_filter
tf.nn.conv3d_backprop_input
tf.nn.conv3d_transpose
tf.nn.convolution
tf.nn.crelu
tf.nn.depthwise_conv2d
tf.nn.depthwise_conv2d_native
tf.nn.depthwise_conv2d_native_backprop_filter
tf.nn.depthwise_conv2d_native_backprop_input
tf.nn.dropout
tf.nn.dynamic_rnn 시험용입니다.
tf.nn.elu
tf.nn.fused_batch_norm
tf.nn.l2_loss
tf.nn.l2_normalize
tf.nn.leaky_relu
tf.nn.local_response_normalization
tf.nn.log_poisson_loss
tf.nn.log_softmax
tf.nn.max_pool
tf.nn.max_pool3d
tf.nn.moments
tf.nn.normalize_moments
tf.nn.pool
tf.nn.relu
tf.nn.relu6
tf.nn.relu_layer
tf.nn.selu
tf.nn.separable_conv2d
tf.nn.sigmoid_cross_entropy_with_logits
tf.nn.softmax
tf.nn.softmax_cross_entropy_with_logits
tf.nn.softplus
tf.nn.softsign
tf.nn.sparse_softmax_cross_entropy_with_logits
tf.nn.static_bidirectional_rnn 시험용입니다.
tf.nn.static_rnn 시험용입니다.
tf.nn.weighted_cross_entropy_with_logits 시험용입니다.
tf.nn.weighted_moments
tf.nn.with_space_to_batch
tf.nn.xw_plus_b
tf.nn.zero_fraction
tf.spectral tf.spectral.fft 시험용입니다.
tf.spectral.fft2d 시험용입니다.
tf.spectral.fft3d 시험용입니다.
tf.spectral.ifft 시험용입니다.
tf.spectral.ifft2d 시험용입니다.
tf.spectral.ifft3d 시험용입니다.
tf.spectral.irfft 실험용입니다. fft_length는 컴파일-시간 상수여야 합니다.
tf.spectral.irfft2d 실험용입니다. fft_length는 컴파일-시간 상수여야 합니다.
tf.spectral.irfft3d 실험용입니다. fft_length는 컴파일-시간 상수여야 합니다.
tf.spectral.rfft 실험용입니다. fft_length는 컴파일-시간 상수여야 합니다.
tf.spectral.rfft2d 실험용입니다. fft_length는 컴파일-시간 상수여야 합니다.
tf.spectral.rfft3d 실험용입니다. fft_length는 컴파일-시간 상수여야 합니다.

사용 불가능한 Python API

이 목록은 일부일 뿐 모든 내용을 포함하지는 않습니다. Cloud TPU에서 사용할 수 없는 오퍼레이션은 다음과 같습니다.

모듈 사용 불가능한 Python API 설명
tf tf.accumulate_n Ref 변수를 사용합니다.
tf.acos
tf.asin
tf.betainc
tf.bitcast
tf.add_check_numerics_ops 숫자 검사 연산자가 포함된 프로그램이 실행되어야 하지만 숫자 검사 연산자가 현재 무시됩니다.
tf.assert_... 어설션이 포함된 프로그램이 실행되어야 하지만 어설션이 무시됩니다.
tf.check_numerics 숫자 검사 연산자가 포함된 프로그램이 실행되어야 하지만 숫자 검사 연산자가 현재 무시됩니다.
tf.confusion_matrix
tf.count_nonzero int64 감소를 사용합니다.
tf.count_up_to
tf.create_partitioned_variables
tf.dequantize
tf.digamma
tf.dynamic_partition
tf.edit_distance
tf.fake_quant_with_min_max_vars_per_channel
tf.fake_quant_with_min_max_vars_per_channel_gradient
tf.histogram_fixed_width
tf.igamma
tf.igammac
tf.lbeta
tf.lgamma
tf.matrix_determinant
tf.matrix_inverse
tf.matrix_solve
tf.matrix_solve_ls
tf.polygamma
tf.py_func
tf.qr
tf.quantize_v2
tf.quantized_concat
tf.random_crop
tf.random_gamma
tf.random_poisson
tf.random_shuffle
tf.scatter_add
tf.scatter_div
tf.scatter_mul
tf.scatter_nd_add
tf.scatter_nd_sub
tf.scatter_nd_update
tf.segment_mean
tf.segment_max
tf.segment_min
tf.segment_prod
tf.segment_sum
tf.self_adjoint_eig
tf.self_adjoint_eigvals
tf.setdiff1d
tf.sparse_...
tf.string_...
tf.substr
tf.svd
tf.to_double
tf.unique
tf.unsorted_segment_max
tf.zeta
tf.bitwise.bitwise_xor
tf.contrib.stateless.stateless_truncated_normal

사용 가능한 그래프 연산자

연산자 유형 제약 조건
Abs T={bfloat16,float,int32,int64}
Acos T={bfloat16,complex64,float,int32,int64}
Acosh T={bfloat16,complex64,float}
Add T={bfloat16,complex64,float,int32,int64}
AddN T={bfloat16,complex64,float,int32,int64,uint32,uint64}
AdjustContrastv2 T={float}
AdjustHue T={float}
AdjustSaturation T={float}
All Tidx={int32,int64}
AllToAll T={bfloat16,float}
Angle Tout={float}
T={complex64}
Any Tidx={int32,int64}
ApproximateEqual T={bfloat16,complex64,float,int32,int64,uint32,uint64}
ArgMax Tidx={int32,int64}
output_type={int32,int64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
ArgMin Tidx={int32,int64}
output_type={int32,int64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
Asin T={bfloat16,complex64,float,int32,int64}
Asinh T={bfloat16,complex64,float}
Assert T={bfloat16,bool,complex64,float,int32,int64,string,uint32,uint64}
AssignAddVariableOp dtype={bfloat16,complex64,float,int32,int64,uint32,uint64}
AssignSubVariableOp dtype={bfloat16,complex64,float,int32,int64,uint32,uint64}
AssignVariableOp dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Atan T={bfloat16,complex64,float,int32,int64}
Atan2 T={bfloat16,float}
Atanh T={bfloat16,complex64,float}
AvgPool T={bfloat16,float}
AvgPool3D T={bfloat16,float}
AvgPool3DGrad T={bfloat16,float}
AvgPoolGrad T={bfloat16,float}
BatchMatMul T={bfloat16,complex64,float,int32,int64}
BatchToSpace Tidx={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
BatchToSpaceND Tcrops={int32,int64}
Tblock_shape={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
BiasAdd T={bfloat16,complex64,float,int32,int64,uint32,uint64}
BiasAddGrad T={bfloat16,complex64,float,int32,int64,uint32,uint64}
BiasAddV1 T={bfloat16,complex64,float,int32,int64,uint32,uint64}
Bitcast type={bfloat16,complex64,float,int32,int64,uint32,uint64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
BitwiseAnd T={int32,int64,uint32,uint64}
BitwiseOr T={int32,int64,uint32,uint64}
BitwiseXor T={int32,int64,uint32,uint64}
BroadcastArgs T={int32,int64}
BroadcastGradientArgs T={int32,int64}
BroadcastTo Tidx={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Bucketize T={float,int32,int64}
Cast DstT={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
SrcT={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Ceil T={bfloat16,float}
CheckNumerics T={bfloat16,float}
Cholesky T={float}
ClipByValue T={bfloat16,complex64,float,int32,int64,uint32,uint64}
CollectivePermute T={bfloat16,float}
Complex Tout={complex64}
T={float}
ComplexAbs Tout={float}
T={complex64}
Concat T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
ConcatOffset
ConcatV2 Tidx={int32}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Conj T={complex64}
ConjugateTranspose Tperm={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Const dtype={bfloat16,bool,complex64,float,int32,int64,string,uint32,uint64}
ControlTrigger
Conv2D T={bfloat16,float}
Conv2DBackpropFilter T={bfloat16,float}
Conv2DBackpropInput T={bfloat16,float}
Conv3D T={bfloat16,float}
Conv3DBackpropFilterV2 T={bfloat16,float}
Conv3DBackpropInputV2 Tshape={int32,int64}
T={bfloat16,float}
Cos T={bfloat16,complex64,float}
Cosh T={bfloat16,complex64,float}
Cross T={bfloat16,float,int32,int64,uint32,uint64}
CrossReplicaSum T={bfloat16,float}
Cumprod Tidx={int32,int64}
T={bfloat16,float,int32}
Cumsum Tidx={int32,int64}
T={bfloat16,float,int32}
DataFormatVecPermute T={int32,int64}
DepthToSpace T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
DepthwiseConv2dNative T={bfloat16,float}
DepthwiseConv2dNativeBackpropFilter T={bfloat16,float}
DepthwiseConv2dNativeBackpropInput T={bfloat16,float}
Diag T={bfloat16,complex64,float,int32,int64}
DiagPart T={bfloat16,complex64,float,int32,int64}
Digamma T={bfloat16,float}
Div T={bfloat16,complex64,float,int32,int64}
DivNoNan T={float}
DynamicStitch T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Elu T={bfloat16,float}
EluGrad T={bfloat16,float}
Empty dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
EmptyTensorList shape_type={int32,int64}
element_dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Equal T={bfloat16,bool,complex64,float,int32,int64}
Erf T={bfloat16,float}
Erfc T={bfloat16,float}
Exp T={bfloat16,complex64,float}
ExpandDims Tdim={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Expm1 T={bfloat16,complex64,float}
ExtractImagePatches T={bfloat16,float,int32,int64,uint32,uint64}
FFT Tcomplex={complex64}
FFT2D Tcomplex={complex64}
FFT3D Tcomplex={complex64}
FakeParam dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
FakeQuantWithMinMaxArgs
FakeQuantWithMinMaxArgsGradient
FakeQuantWithMinMaxVars
FakeQuantWithMinMaxVarsGradient
Fill index_type={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Floor T={bfloat16,float}
FloorDiv T={bfloat16,complex64,float,int32,int64}
FloorMod T={bfloat16,float,int32,int64}
FusedBatchNorm T={float}
FusedBatchNormGrad T={float}
FusedBatchNormGradV2 U={float}
T={bfloat16,float}
FusedBatchNormV2 U={float}
T={bfloat16,float}
Gather Tindices={int32,int64}
Tparams={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
GatherNd Tindices={int32,int64}
Tparams={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
GatherV2 Taxis={int32,int64}
Tindices={int32,int64}
Tparams={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
GetItem T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Greater T={bfloat16,float,int32,int64,uint32,uint64}
GreaterEqual T={bfloat16,float,int32,int64,uint32,uint64}
HSVToRGB T={bfloat16,float}
IFFT Tcomplex={complex64}
IFFT2D Tcomplex={complex64}
IFFT3D Tcomplex={complex64}
IRFFT
IRFFT2D
IRFFT3D
Identity T={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
IdentityN T={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
If Tout={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
Tin={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
Tcond={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
Imag Tout={float}
T={complex64}
InfeedDequeue dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
InfeedDequeueTuple dtypes={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
InplaceAdd T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
InplaceUpdate T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Inv T={bfloat16,complex64,float,int32,int64}
Invert T={int32,int64,uint32,uint64}
InvertPermutation T={int32}
IsFinite T={bfloat16,float}
IsInf T={bfloat16,float}
IsNan T={bfloat16,float}
L2Loss T={bfloat16,float}
LRN T={bfloat16,float}
LRNGrad T={bfloat16,float}
LeakyRelu T={bfloat16,float}
LeakyReluGrad T={bfloat16,float}
LeftShift T={int32,int64,uint32,uint64}
Less T={bfloat16,float,int32,int64,uint32,uint64}
LessEqual T={bfloat16,float,int32,int64,uint32,uint64}
Lgamma T={bfloat16,float}
LinSpace Tidx={int32,int64}
T={bfloat16,float}
ListDiff out_idx={int32,int64}
T={int32,int64}
Log T={bfloat16,complex64,float}
Log1p T={bfloat16,complex64,float}
LogSoftmax T={bfloat16,float}
LogicalAnd
LogicalNot
LogicalOr
MatMul T={bfloat16,complex64,float}
MatrixBandPart Tindex={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
MatrixDiag T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
MatrixDiagPart T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
MatrixSetDiag T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
MatrixTriangularSolve T={complex64,float}
Max Tidx={int32,int64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
MaxPool T={bfloat16,float,int32,int64}
MaxPool3D T={bfloat16,float}
MaxPool3DGrad TInput={bfloat16,float}
T={bfloat16,float}
MaxPool3DGradGrad T={float}
MaxPoolGrad T={bfloat16,float,int32,int64,uint32,uint64}
MaxPoolGradGrad T={float}
MaxPoolGradGradV2 T={float}
MaxPoolGradV2 T={bfloat16,float,int32,int64,uint32,uint64}
MaxPoolV2 T={bfloat16,float,int32,int64}
Maximum T={bfloat16,float,int32,int64}
Mean Tidx={int32,int64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
Min Tidx={int32,int64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
Minimum T={bfloat16,float,int32,int64}
MirrorPad Tpaddings={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Mod T={bfloat16,float,int32,int64}
Mul T={bfloat16,complex64,float,int32,int64}
Multinomial output_dtype={int32,int64}
T={bfloat16,float,int32,int64,uint32,uint64}
Neg T={bfloat16,complex64,float,int32,int64}
NoOp
NonMaxSuppressionV4 T={float}
NotEqual T={bfloat16,bool,complex64,float,int32,int64}
OneHot TI={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
OnesLike T={bfloat16,bool,complex64,float,int32,int64}
OutfeedEnqueue dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
OutfeedEnqueueTuple dtypes={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Pack T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Pad Tpaddings={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
PadV2 Tpaddings={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
ParallelDynamicStitch T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
PlaceholderWithDefault dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Pow T={bfloat16,complex64,float,int32,int64}
PreventGradient T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Prod Tidx={int32,int64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
Qr T={float}
QuantizeAndDequantizeV2 T={bfloat16,float}
QuantizeAndDequantizeV3 T={bfloat16,float}
RFFT
RFFT2D
RFFT3D
RGBToHSV T={bfloat16,float}
RandomShuffle T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
RandomStandardNormal T={int32,int64}
dtype={bfloat16,float}
RandomUniform T={int32,int64}
dtype={bfloat16,float}
RandomUniformInt T={int32,int64}
Tout={int32,int64}
Range Tidx={bfloat16,float,int32,int64}
Rank T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
ReadVariableOp dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Real Tout={float}
T={complex64}
RealDiv T={bfloat16,complex64,float,int32,int64}
Reciprocal T={bfloat16,complex64,float,int32,int64}
ReciprocalGrad T={bfloat16,complex64,float}
RecvTPUEmbeddingActivations
Relu T={bfloat16,float,int32,int64,uint32,uint64}
Relu6 T={bfloat16,float,int32,int64,uint32,uint64}
Relu6Grad T={bfloat16,float,int32,int64,uint32,uint64}
ReluGrad T={bfloat16,float,int32,int64,uint32,uint64}
Reshape Tshape={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
ResizeBilinear T={bfloat16,float,int32,int64}
ResizeBilinearGrad T={bfloat16,float}
ResizeNearestNeighbor T={float,int32,int64}
ResourceApplyAdaMax T={bfloat16,float}
ResourceApplyAdadelta T={bfloat16,float}
ResourceApplyAdagrad T={bfloat16,float}
ResourceApplyAdagradDA T={bfloat16,float}
ResourceApplyAdam T={bfloat16,float}
ResourceApplyAddSign T={bfloat16,float}
ResourceApplyCenteredRMSProp T={bfloat16,float}
ResourceApplyFtrl T={bfloat16,float}
ResourceApplyFtrlV2 T={bfloat16,float}
ResourceApplyGradientDescent T={bfloat16,float}
ResourceApplyKerasMomentum T={bfloat16,float}
ResourceApplyMomentum T={bfloat16,float}
ResourceApplyPowerSign T={bfloat16,float}
ResourceApplyProximalAdagrad T={bfloat16,float}
ResourceApplyProximalGradientDescent T={bfloat16,float}
ResourceApplyRMSProp T={bfloat16,float}
ResourceGather Tindices={int32,int64}
dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
ResourceScatterAdd Tindices={int32,int64}
dtype={bfloat16,complex64,float,int32,int64,uint32,uint64}
ResourceScatterDiv Tindices={int32,int64}
dtype={bfloat16,complex64,float,int32,int64,uint32,uint64}
ResourceScatterMax Tindices={int32,int64}
dtype={bfloat16,complex64,float,int32,int64,uint32,uint64}
ResourceScatterMin Tindices={int32,int64}
dtype={bfloat16,complex64,float,int32,int64,uint32,uint64}
ResourceScatterMul Tindices={int32,int64}
dtype={bfloat16,complex64,float,int32,int64,uint32,uint64}
ResourceScatterNdAdd Tindices={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
ResourceScatterNdSub Tindices={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
ResourceScatterNdUpdate Tindices={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
ResourceScatterSub Tindices={int32,int64}
dtype={bfloat16,complex64,float,int32,int64,uint32,uint64}
ResourceScatterUpdate Tindices={int32,int64}
dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
ResourceStridedSliceAssign Index={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Reverse T={bool,complex64,float,int32,int64}
ReverseSequence Tlen={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
ReverseV2 T={bfloat16,bool,complex64,float,int32,int64}
Tidx={int32,int64}
RightShift T={int32,int64,uint32,uint64}
Rint T={bfloat16,float}
Round T={bfloat16,complex64,float,int32,int64}
Rsqrt T={bfloat16,complex64,float}
RsqrtGrad T={bfloat16,complex64,float}
ScatterNd Tindices={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Select T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Selu T={bfloat16,float}
SeluGrad T={bfloat16,float}
SendTPUEmbeddingGradients
Shape out_type={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
ShapeN out_type={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Sigmoid T={bfloat16,complex64,float}
SigmoidGrad T={bfloat16,complex64,float}
Sign T={bfloat16,complex64,float,int32,int64}
Sin T={bfloat16,complex64,float}
Sinh T={bfloat16,complex64,float}
Size out_type={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Slice Index={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Snapshot T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Softmax T={bfloat16,float}
SoftmaxCrossEntropyWithLogits T={bfloat16,float}
Softplus T={bfloat16,float}
SoftplusGrad T={bfloat16,float}
Softsign T={bfloat16,float}
SoftsignGrad T={bfloat16,float}
SpaceToBatch Tpaddings={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
SpaceToBatchND Tblock_shape={int32,int64}
Tpaddings={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
SpaceToDepth T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
SparseMatMul Tb={bfloat16,float}
Ta={bfloat16,float}
SparseSoftmaxCrossEntropyWithLogits Tlabels={int32,int64}
T={bfloat16,float}
SparseToDense Tindices={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Split T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
SplitV Tlen={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Sqrt T={bfloat16,complex64,float}
SqrtGrad T={bfloat16,complex64,float}
Square T={bfloat16,complex64,float,int32,int64}
SquaredDifference T={bfloat16,complex64,float,int32,int64}
Squeeze T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
StackCloseV2
StackPopV2 elem_type={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
StackPushV2 T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
StackV2 elem_type={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
StatelessIf Tout={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
Tin={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
Tcond={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
StatelessMultinomial output_dtype={int32,int64}
Tseed={int32}
T={bfloat16,float}
StatelessRandomNormal Tseed={int32}
T={int32,int64}
dtype={bfloat16,float}
StatelessRandomUniform Tseed={int32}
T={int32,int64}
dtype={bfloat16,float}
StatelessRandomUniformInt Tseed={int32}
T={int32,int64}
dtype={int32,int64}
StatelessTruncatedNormal Tseed={int32}
T={int32,int64}
dtype={bfloat16,float}
StatelessWhile T={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
StopGradient T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
StridedSlice Index={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
StridedSliceGrad Index={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Sub T={bfloat16,complex64,float,int32,int64}
Sum Tidx={int32,int64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
SymbolicGradient Tout={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Tin={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
TPUEmbeddingActivations
Tan T={bfloat16,complex64,float,int32,int64}
Tanh T={bfloat16,complex64,float}
TanhGrad T={bfloat16,complex64,float}
TensorArrayCloseV3
TensorArrayConcatV3 dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
TensorArrayGatherV3 dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
TensorArrayGradV3
TensorArrayReadV3 dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
TensorArrayScatterV3 T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
TensorArraySizeV3
TensorArraySplitV3 T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
TensorArrayV3 dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
TensorArrayWriteV3 T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
TensorListElementShape shape_type={int32,int64}
TensorListPopBack element_dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
TensorListPushBack element_dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
TensorListReserve shape_type={int32,int64}
element_dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Tile Tmultiples={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
TopKV2 T={bfloat16,float,int32,uint32}
Transpose Tperm={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
TruncateDiv T={bfloat16,complex64,float,int32,int64}
TruncateMod T={bfloat16,float,int32,int64}
TruncatedNormal T={int32,int64}
dtype={float}
Unpack T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
UnsortedSegmentMax Tnumsegments={int32,int64}
Tindices={int32,int64}
T={bfloat16,float,int32,int64,uint32,uint64}
UnsortedSegmentMin Tnumsegments={int32,int64}
Tindices={int32,int64}
T={bfloat16,float,int32,int64,uint32,uint64}
UnsortedSegmentProd Tnumsegments={int32,int64}
Tindices={int32,int64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
UnsortedSegmentSum Tnumsegments={int32,int64}
Tindices={int32,int64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
VarIsInitializedOp
VariableShape out_type={int32,int64}
While T={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
Xdivy T={complex64,float}
XlaBroadcastHelper Tindices={int32,int64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
XlaConv Tindices={int32,int64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
XlaDequantize
XlaDot T={bfloat16,complex64,float,int32,int64,uint32,uint64}
XlaDynamicSlice Tindices={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
XlaDynamicUpdateSlice Tindices={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
XlaHostCompute Toutputs={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Tinputs={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
XlaIf Tout={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
Tin={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
Tcond={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
XlaKeyValueSort V={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
K={bfloat16,float,int32,int64,uint32,uint64}
XlaPad Tindices={int32,int64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
XlaRecv dtype={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
XlaRecvFromHost Toutput={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
XlaReduce T={bfloat16,complex64,float,int32,int64,uint32,uint64}
XlaReduceWindow Tindices={int32,int64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
XlaSelectAndScatter Tindices={int32,int64}
T={bfloat16,complex64,float,int32,int64,uint32,uint64}
XlaSend T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
XlaSendToHost Tinput={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
XlaSort T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
XlaWhile T={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
Xlogy T={complex64,float}
ZerosLike T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
_Arg T={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}
_ArrayToList out_types={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
_ListToArray T={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
Tin={bfloat16,bool,complex64,float,int32,int64,uint32,uint64}
_Retval T={bfloat16,bool,complex64,float,int32,int64,resource,uint32,uint64}