sample
float32[batch_size,num_channels,height,width]
Cast
graph_input_cast0
Conv
/encoder/conv_in/Conv
float16[128,3,3,3]
W
〈128×3×3×3〉
float16[128]
B
〈128〉
Transpose
Transpose_NCHW_to_NHWC_0
GroupNorm
GroupNorm_0
float32[128]
gamma
〈128〉
float32[128]
beta
〈128〉
Transpose
Transpose_NHWC_to_NCHW_0
Conv
/encoder/down_blocks.0/resnets.0/conv1/Conv
float16[128,128,3,3]
W
〈128×128×3×3〉
float16[128]
B
〈128〉
Transpose
Transpose_NCHW_to_NHWC_1
GroupNorm
GroupNorm_1
float32[128]
gamma
〈128〉
float32[128]
beta
〈128〉
Transpose
Transpose_NHWC_to_NCHW_1
Conv
/encoder/down_blocks.0/resnets.0/conv2/Conv
float16[128,128,3,3]
W
〈128×128×3×3〉
float16[128]
B
〈128〉
Add
/encoder/down_blocks.0/resnets.0/Add
Transpose
Transpose_NCHW_to_NHWC_2
GroupNorm
GroupNorm_2
float32[128]
gamma
〈128〉
float32[128]
beta
〈128〉
Transpose
Transpose_NHWC_to_NCHW_2
Conv
/encoder/down_blocks.0/resnets.1/conv1/Conv
float16[128,128,3,3]
W
〈128×128×3×3〉
float16[128]
B
〈128〉
Transpose
Transpose_NCHW_to_NHWC_3
GroupNorm
GroupNorm_3
float32[128]
gamma
〈128〉
float32[128]
beta
〈128〉
Transpose
Transpose_NHWC_to_NCHW_3
Conv
/encoder/down_blocks.0/resnets.1/conv2/Conv
float16[128,128,3,3]
W
〈128×128×3×3〉
float16[128]
B
〈128〉
Add
/encoder/down_blocks.0/resnets.1/Add
Pad
/encoder/down_blocks.0/downsamplers.0/Pad
int64[8]
pads
〈8〉
float16
constant_value
= 0
Conv
/encoder/down_blocks.0/downsamplers.0/conv/Conv
float16[128,128,3,3]
W
〈128×128×3×3〉
float16[128]
B
〈128〉
Conv
/encoder/down_blocks.1/resnets.0/conv_shortcut/Conv
float16[256,128,1,1]
W
〈256×128×1×1〉
float16[256]
B
〈256〉
Transpose
Transpose_NCHW_to_NHWC_4
GroupNorm
GroupNorm_4
float32[128]
gamma
〈128〉
float32[128]
beta
〈128〉
Transpose
Transpose_NHWC_to_NCHW_4
Conv
/encoder/down_blocks.1/resnets.0/conv1/Conv
float16[256,128,3,3]
W
〈256×128×3×3〉
float16[256]
B
〈256〉
Transpose
Transpose_NCHW_to_NHWC_5
GroupNorm
GroupNorm_5
float32[256]
gamma
〈256〉
float32[256]
beta
〈256〉
Transpose
Transpose_NHWC_to_NCHW_5
Conv
/encoder/down_blocks.1/resnets.0/conv2/Conv
float16[256,256,3,3]
W
〈256×256×3×3〉
float16[256]
B
〈256〉
Add
/encoder/down_blocks.1/resnets.0/Add
Transpose
Transpose_NCHW_to_NHWC_6
GroupNorm
GroupNorm_6
float32[256]
gamma
〈256〉
float32[256]
beta
〈256〉
Transpose
Transpose_NHWC_to_NCHW_6
Conv
/encoder/down_blocks.1/resnets.1/conv1/Conv
float16[256,256,3,3]
W
〈256×256×3×3〉
float16[256]
B
〈256〉
Transpose
Transpose_NCHW_to_NHWC_7
GroupNorm
GroupNorm_7
float32[256]
gamma
〈256〉
float32[256]
beta
〈256〉
Transpose
Transpose_NHWC_to_NCHW_7
Conv
/encoder/down_blocks.1/resnets.1/conv2/Conv
float16[256,256,3,3]
W
〈256×256×3×3〉
float16[256]
B
〈256〉
Add
/encoder/down_blocks.1/resnets.1/Add
Pad
/encoder/down_blocks.1/downsamplers.0/Pad
int64[8]
pads
〈8〉
float16
constant_value
= 0
Conv
/encoder/down_blocks.1/downsamplers.0/conv/Conv
float16[256,256,3,3]
W
〈256×256×3×3〉
float16[256]
B
〈256〉
Conv
/encoder/down_blocks.2/resnets.0/conv_shortcut/Conv
float16[512,256,1,1]
W
〈512×256×1×1〉
float16[512]
B
〈512〉
Transpose
Transpose_NCHW_to_NHWC_8
GroupNorm
GroupNorm_8
float32[256]
gamma
〈256〉
float32[256]
beta
〈256〉
Transpose
Transpose_NHWC_to_NCHW_8
Conv
/encoder/down_blocks.2/resnets.0/conv1/Conv
float16[512,256,3,3]
W
〈512×256×3×3〉
float16[512]
B
〈512〉
Transpose
Transpose_NCHW_to_NHWC_9
GroupNorm
GroupNorm_9
float32[512]
gamma
〈512〉
float32[512]
beta
〈512〉
Transpose
Transpose_NHWC_to_NCHW_9
Conv
/encoder/down_blocks.2/resnets.0/conv2/Conv
float16[512,512,3,3]
W
〈512×512×3×3〉
float16[512]
B
〈512〉
Add
/encoder/down_blocks.2/resnets.0/Add
Transpose
Transpose_NCHW_to_NHWC_10
GroupNorm
GroupNorm_10
float32[512]
gamma
〈512〉
float32[512]
beta
〈512〉
Transpose
Transpose_NHWC_to_NCHW_10
Conv
/encoder/down_blocks.2/resnets.1/conv1/Conv
float16[512,512,3,3]
W
〈512×512×3×3〉
float16[512]
B
〈512〉
Transpose
Transpose_NCHW_to_NHWC_11
GroupNorm
GroupNorm_11
float32[512]
gamma
〈512〉
float32[512]
beta
〈512〉
Transpose
Transpose_NHWC_to_NCHW_11
Conv
/encoder/down_blocks.2/resnets.1/conv2/Conv
float16[512,512,3,3]
W
〈512×512×3×3〉
float16[512]
B
〈512〉
Add
/encoder/down_blocks.2/resnets.1/Add
Pad
/encoder/down_blocks.2/downsamplers.0/Pad
int64[8]
pads
〈8〉
float16
constant_value
= 0
Conv
/encoder/down_blocks.2/downsamplers.0/conv/Conv
float16[512,512,3,3]
W
〈512×512×3×3〉
float16[512]
B
〈512〉
Transpose
Transpose_NCHW_to_NHWC_12
GroupNorm
GroupNorm_12
float32[512]
gamma
〈512〉
float32[512]
beta
〈512〉
Transpose
Transpose_NHWC_to_NCHW_12
Conv
/encoder/down_blocks.3/resnets.0/conv1/Conv
float16[512,512,3,3]
W
〈512×512×3×3〉
float16[512]
B
〈512〉
Transpose
Transpose_NCHW_to_NHWC_13
GroupNorm
GroupNorm_13
float32[512]
gamma
〈512〉
float32[512]
beta
〈512〉
Transpose
Transpose_NHWC_to_NCHW_13
Conv
/encoder/down_blocks.3/resnets.0/conv2/Conv
float16[512,512,3,3]
W
〈512×512×3×3〉
float16[512]
B
〈512〉
Add
/encoder/down_blocks.3/resnets.0/Add
Transpose
Transpose_NCHW_to_NHWC_14
GroupNorm
GroupNorm_14
float32[512]
gamma
〈512〉
float32[512]
beta
〈512〉
Transpose
Transpose_NHWC_to_NCHW_14
Conv
/encoder/down_blocks.3/resnets.1/conv1/Conv
float16[512,512,3,3]
W
〈512×512×3×3〉
float16[512]
B
〈512〉
Transpose
Transpose_NCHW_to_NHWC_15
GroupNorm
GroupNorm_15
float32[512]
gamma
〈512〉
float32[512]
beta
〈512〉
Transpose
Transpose_NHWC_to_NCHW_15
Conv
/encoder/down_blocks.3/resnets.1/conv2/Conv
float16[512,512,3,3]
W
〈512×512×3×3〉
float16[512]
B
〈512〉
Add
/encoder/down_blocks.3/resnets.1/Add
Transpose
Transpose_NCHW_to_NHWC_16
GroupNorm
GroupNorm_16
float32[512]
gamma
〈512〉
float32[512]
beta
〈512〉
Transpose
Transpose_NHWC_to_NCHW_16
Conv
/encoder/mid_block/resnets.0/conv1/Conv
float16[512,512,3,3]
W
〈512×512×3×3〉
float16[512]
B
〈512〉
Transpose
Transpose_NCHW_to_NHWC_17
GroupNorm
GroupNorm_17
float32[512]
gamma
〈512〉
float32[512]
beta
〈512〉
Transpose
Transpose_NHWC_to_NCHW_17
Conv
/encoder/mid_block/resnets.0/conv2/Conv
float16[512,512,3,3]
W
〈512×512×3×3〉
float16[512]
B
〈512〉
Add
/encoder/mid_block/resnets.0/Add
Shape
/encoder/mid_block/attentions.0/Shape_3
Gather
/encoder/mid_block/attentions.0/Gather_3
int64
indices
= 3
Unsqueeze
/encoder/mid_block/attentions.0/Unsqueeze_14
int64[1]
axes
〈1〉
Gather
/encoder/mid_block/attentions.0/Gather_2
int64
indices
= 2
Unsqueeze
/encoder/mid_block/attentions.0/Unsqueeze_13
int64[1]
axes
〈1〉
Gather
/encoder/mid_block/attentions.0/Gather_1
int64
indices
= 1
Unsqueeze
/encoder/mid_block/attentions.0/Unsqueeze_12
int64[1]
axes
〈1〉
Reshape
/encoder/mid_block/attentions.0/Reshape
int64[3]
shape
〈3〉
Shape
/encoder/mid_block/attentions.0/Shape_4
Gather
Gather
int64[3]
indices
〈3〉
Gather
/encoder/mid_block/attentions.0/Gather_4
int64
indices
= 0
Unsqueeze
/encoder/mid_block/attentions.0/Unsqueeze_11
int64[1]
axes
〈1〉
Concat
/encoder/mid_block/attentions.0/Concat_5
Reshape
/encoder/mid_block/attentions.0/group_norm/Reshape
int64[3]
shape
〈3〉
InstanceNormalization
/encoder/mid_block/attentions.0/group_norm/InstanceNormalization
float16[32]
scale
〈32〉
float16[32]
B
〈32〉
Reshape
/encoder/mid_block/attentions.0/group_norm/Reshape_1
Mul
/encoder/mid_block/attentions.0/group_norm/Mul
float16[512,1]
B
〈512×1〉
Add
/encoder/mid_block/attentions.0/group_norm/Add
float16[512,1]
B
〈512×1〉
Transpose
/encoder/mid_block/attentions.0/Transpose_1
MatMul
/encoder/mid_block/attentions.0/to_k/MatMul
float16[512,512]
B
〈512×512〉
Add
/encoder/mid_block/attentions.0/to_k/Add
float16[512]
A
〈512〉
Shape
/encoder/mid_block/attentions.0/Shape_5
Gather
/encoder/mid_block/attentions.0/Gather_5
int64
indices
= 2
Unsqueeze
/encoder/mid_block/attentions.0/Unsqueeze_10
int64[1]
axes
〈1〉
Unsqueeze
/encoder/mid_block/attentions.0/Unsqueeze_9
int64[1]
axes
〈1〉
Concat
/encoder/mid_block/attentions.0/Concat_4
〈…〉
Unsqueeze
/encoder/mid_block/attentions.0/Unsqueeze_4
int64[1]
axes
〈1〉
Unsqueeze
/encoder/mid_block/attentions.0/Unsqueeze_3
int64[1]
axes
〈1〉
Concat
/encoder/mid_block/attentions.0/Concat_1
〈…〉
MatMul
/encoder/mid_block/attentions.0/to_q/MatMul
float16[512,512]
B
〈512×512〉
Add
/encoder/mid_block/attentions.0/to_q/Add
float16[512]
A
〈512〉
Reshape
/encoder/mid_block/attentions.0/Reshape_1
Shape
/encoder/mid_block/attentions.0/Shape_6
Gather
Gather_token_1
int64[4]
indices
〈4〉
Slice
/encoder/mid_block/attentions.0/Slice
int64[1]
starts
〈1〉
int64[1]
ends
〈1〉
Cast
/encoder/mid_block/attentions.0/Cast_2
Sqrt
/encoder/mid_block/attentions.0/Sqrt
Div
/encoder/mid_block/attentions.0/Div_1
float16[1]
A
〈1〉
Sqrt
/encoder/mid_block/attentions.0/Sqrt_2
Unsqueeze
/encoder/mid_block/attentions.0/Unsqueeze_6
int64[1]
axes
〈1〉
Unsqueeze
/encoder/mid_block/attentions.0/Unsqueeze_5
int64[1]
axes
〈1〉
Concat
/encoder/mid_block/attentions.0/Concat_2
〈…〉
Reshape
/encoder/mid_block/attentions.0/Reshape_2
Transpose
/encoder/mid_block/attentions.0/Transpose_4
Mul
/encoder/mid_block/attentions.0/Mul_2
Transpose
/encoder/mid_block/attentions.0/Transpose_2
Mul
/encoder/mid_block/attentions.0/Mul_1
MatMul
/encoder/mid_block/attentions.0/MatMul
Softmax
/encoder/mid_block/attentions.0/Softmax
Unsqueeze
/encoder/mid_block/attentions.0/Unsqueeze_8
int64[1]
axes
〈1〉
Unsqueeze
/encoder/mid_block/attentions.0/Unsqueeze_7
int64[1]
axes
〈1〉
Concat
/encoder/mid_block/attentions.0/Concat_3
〈…〉
MatMul
/encoder/mid_block/attentions.0/to_v/MatMul
float16[512,512]
B
〈512×512〉
Add
/encoder/mid_block/attentions.0/to_v/Add
float16[512]
A
〈512〉
Reshape
/encoder/mid_block/attentions.0/Reshape_3
Transpose
/encoder/mid_block/attentions.0/Transpose_3
MatMul
/encoder/mid_block/attentions.0/MatMul_1
Transpose
/encoder/mid_block/attentions.0/Transpose_5
Reshape
/encoder/mid_block/attentions.0/Reshape_4
MatMul
/encoder/mid_block/attentions.0/to_out.0/MatMul
float16[512,512]
B
〈512×512〉
Add
/encoder/mid_block/attentions.0/to_out.0/Add
float16[512]
A
〈512〉
Transpose
/encoder/mid_block/attentions.0/Transpose_6
Reshape
/encoder/mid_block/attentions.0/Reshape_5
Add
/encoder/mid_block/attentions.0/Add
Transpose
Transpose_NCHW_to_NHWC_18
GroupNorm
GroupNorm_18
float32[512]
gamma
〈512〉
float32[512]
beta
〈512〉
Transpose
Transpose_NHWC_to_NCHW_18
Conv
/encoder/mid_block/resnets.1/conv1/Conv
float16[512,512,3,3]
W
〈512×512×3×3〉
float16[512]
B
〈512〉
Transpose
Transpose_NCHW_to_NHWC_19
GroupNorm
GroupNorm_19
float32[512]
gamma
〈512〉
float32[512]
beta
〈512〉
Transpose
Transpose_NHWC_to_NCHW_19
Conv
/encoder/mid_block/resnets.1/conv2/Conv
float16[512,512,3,3]
W
〈512×512×3×3〉
float16[512]
B
〈512〉
Add
/encoder/mid_block/resnets.1/Add
Transpose
Transpose_NCHW_to_NHWC_20
GroupNorm
GroupNorm_20
float32[512]
gamma
〈512〉
float32[512]
beta
〈512〉
Transpose
Transpose_NHWC_to_NCHW_20
Conv
/encoder/conv_out/Conv
float16[8,512,3,3]
W
〈8×512×3×3〉
float16[8]
B
〈8〉
Conv
/quant_conv/Conv
float16[8,8,1,1]
W
〈8×8×1×1〉
float16[8]
B
〈8〉
Shape
/Shape
Gather
/Gather
int64[1]
indices
〈1〉
Add
/Add
int64[1]
B
〈1〉
Div
/Div
int64[1]
B
〈1〉
Slice
/Slice
int64[1]
starts
〈1〉
int64[1]
axes
〈1〉
Shape
/Shape_4
ConstantOfShape
/ConstantOfShape
Mul
/Mul_1
int64[1]
B
〈1〉
Slice
/Slice_1
int64[1]
axes
〈1〉
Clip
/Clip
float16
min
= -30
float16
max
= 20
Mul
/Mul_2
float16
B
= 0.5
Exp
/Exp
Cast
/RandomNormalLike_input_cast0
RandomNormalLike
/RandomNormalLike
Cast
/RandomNormalLike_output_cast0
Mul
/Mul_3
Add
/Add_1
Cast
graph_output_cast0
latent_sample
float32[batch_size,num_channels_latent,height_latent,width_latent]
×
torch_jit
❮
Version
{version}
Copyright ©
Lutz Roeder
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