torch.jit.frontend.UnsupportedNodeError: JoinedStr aren't supported

[YanADingggg]

I tried to run this program under the environment and torch specified by the author, but this error occurred. Could you please help me check it? Thank you very much

Traceback (most recent call last): File "train.py", line 10, in import model.model as module_arch File "/home/cas/桌面/jack/EESRGAN-master/model/model.py", line 7, in import kornia File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/kornia/init.py", line 13, in from kornia import augmentation, color, contrib, enhance, feature, filters, geometry, jit, losses, morphology, utils File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/kornia/jit/init.py", line 7, in grayscale_to_rgb = torch.jit.script(K.color.grayscale_to_rgb) File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/init.py", line 823, in script ast = get_jit_def(obj) File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 158, in get_jit_def return build_def(ctx, py_ast.body[0], type_line, self_name) File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 198, in build_def build_stmts(ctx, body)) File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 122, in build_stmts stmts = [build_stmt(ctx, s) for s in stmts] File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 122, in stmts = [build_stmt(ctx, s) for s in stmts] File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 174, in call return method(ctx, node) File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 332, in build_If build_stmts(ctx, stmt.body), File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 122, in build_stmts stmts = [build_stmt(ctx, s) for s in stmts] File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 122, in stmts = [build_stmt(ctx, s) for s in stmts] File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 174, in call return method(ctx, node) File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 288, in build_Raise expr = build_expr(ctx, stmt.exc) File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 174, in call return method(ctx, node) File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 405, in build_Call args = [build_expr(ctx, py_arg) for py_arg in expr.args] File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 405, in args = [build_expr(ctx, py_arg) for py_arg in expr.args] File "/home/cas/anaconda3/envs/deep-learning/lib/python3.7/site-packages/torch/jit/frontend.py", line 173, in call raise UnsupportedNodeError(ctx, node) torch.jit.frontend.UnsupportedNodeError: JoinedStr aren't supported image: grayscale image to be converted to RGB with shape :math:(*,1,H,W). Returns: RGB version of the image with shape :math:(*,3,H,W).

Example:
    >>> input = torch.randn(2, 1, 4, 5)
    >>> gray = grayscale_to_rgb(input) # 2x3x4x5
"""
if not isinstance(image, torch.Tensor):
    raise TypeError(f"Input type is not a torch.Tensor. " f"Got {type(image)}")
                    ~ <--- HERE
if image.dim() < 3 or image.size(-3) != 1:
    raise ValueError(f"Input size must have a shape of (*, 1, H, W). " f"Got {image.shape}.")
rgb: torch.Tensor = torch.cat([image, image, image], dim=-3)
image_is_float: bool = torch.is_floating_point(image)
if not image_is_float:
    warnings.warn(f"Input image is not of float dtype. Got {image.dtype}")
return rgb

[TriBall3]

I met the same problem with you , did you solve this?