try:
import tensorflow as tf
except ImportError:
tf = None
try:
from torch import nn
except ImportError:
nn = None
[docs]
def model_to_spec(model) -> str:
"""
Convert a deep learning model (TensorFlow or PyTorch) to a VGSL spec string.
Parameters
----------
model : Model
The deep learning model to be converted. Can be a TensorFlow model (tf.keras.models.Model)
or a PyTorch model (torch.nn.Module).
Returns
-------
str
VGSL spec string.
Raises
------
ValueError
If the model is not supported or cannot be parsed.
Examples
--------
>>> from vgslify.utils import model_to_spec
>>> import tensorflow as tf
>>> model = tf.keras.models.load_model("path_to_model.h5")
>>> spec_string = model_to_spec(model)
>>> print(spec_string)
"""
# Check if it's a TensorFlow model
if tf and isinstance(model, tf.keras.Model):
from vgslify.parser.tf_parser import tf_to_spec
return tf_to_spec(model)
# Check if it's a PyTorch model
if nn and isinstance(model, nn.Module):
raise NotImplementedError("PyTorch models are not supported yet.")
# Raise an error if the model is not recognized
raise ValueError(
f"Unsupported model type: {type(model).__name__}. Expected TensorFlow "
"or PyTorch model.")