implement train api

2 files changed, 30 insertions, 27 deletions

diff --git a/modules/hypernetworks/hypernetwork.py b/modules/hypernetworks/hypernetwork.py
index c406ffb3..3182ff03 100644
--- a/modules/hypernetworks/hypernetwork.py
+++ b/modules/hypernetworks/hypernetwork.py
@@ -378,6 +378,32 @@ def report_statistics(loss_info:dict):
             print(e)

 

 

+def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False):

+    # Remove illegal characters from name.

+    name = "".join( x for x in name if (x.isalnum() or x in "._- "))

+

+    fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")

+    if not overwrite_old:

+        assert not os.path.exists(fn), f"file {fn} already exists"

+

+    if type(layer_structure) == str:

+        layer_structure = [float(x.strip()) for x in layer_structure.split(",")]

+

+    hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(

+        name=name,

+        enable_sizes=[int(x) for x in enable_sizes],

+        layer_structure=layer_structure,

+        activation_func=activation_func,

+        weight_init=weight_init,

+        add_layer_norm=add_layer_norm,

+        use_dropout=use_dropout,

+    )

+    hypernet.save(fn)

+

+    shared.reload_hypernetworks()

+

+    return fn

+

 

 def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step, data_root, log_directory, training_width, training_height, steps, shuffle_tags, tag_drop_out, latent_sampling_method, create_image_every, save_hypernetwork_every, template_file, preview_from_txt2img, preview_prompt, preview_negative_prompt, preview_steps, preview_sampler_index, preview_cfg_scale, preview_seed, preview_width, preview_height):

     # images allows training previews to have infotext. Importing it at the top causes a circular import problem.

diff --git a/modules/hypernetworks/ui.py b/modules/hypernetworks/ui.py
index c2d4b51c..e7f9e593 100644
--- a/modules/hypernetworks/ui.py
+++ b/modules/hypernetworks/ui.py
@@ -3,39 +3,16 @@ import os
 import re

 

 import gradio as gr

-import modules.textual_inversion.preprocess

-import modules.textual_inversion.textual_inversion

+import modules.hypernetworks.hypernetwork

 from modules import devices, sd_hijack, shared

-from modules.hypernetworks import hypernetwork

 

 not_available = ["hardswish", "multiheadattention"]

-keys = list(x for x in hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available)

+keys = list(x for x in modules.hypernetworks.hypernetwork.HypernetworkModule.activation_dict.keys() if x not in not_available)

 

 def create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure=None, activation_func=None, weight_init=None, add_layer_norm=False, use_dropout=False):

-    # Remove illegal characters from name.

-    name = "".join( x for x in name if (x.isalnum() or x in "._- "))

+    filename = modules.hypernetworks.hypernetwork.create_hypernetwork(name, enable_sizes, overwrite_old, layer_structure, activation_func, weight_init, add_layer_norm, use_dropout)

 

-    fn = os.path.join(shared.cmd_opts.hypernetwork_dir, f"{name}.pt")

-    if not overwrite_old:

-        assert not os.path.exists(fn), f"file {fn} already exists"

-

-    if type(layer_structure) == str:

-        layer_structure = [float(x.strip()) for x in layer_structure.split(",")]

-

-    hypernet = modules.hypernetworks.hypernetwork.Hypernetwork(

-        name=name,

-        enable_sizes=[int(x) for x in enable_sizes],

-        layer_structure=layer_structure,

-        activation_func=activation_func,

-        weight_init=weight_init,

-        add_layer_norm=add_layer_norm,

-        use_dropout=use_dropout,

-    )

-    hypernet.save(fn)

-

-    shared.reload_hypernetworks()

-

-    return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {fn}", ""

+    return gr.Dropdown.update(choices=sorted([x for x in shared.hypernetworks.keys()])), f"Created: {filename}", ""

 

 

 def train_hypernetwork(*args):