tidy

notebooks/test_model.ipynb

@@ -429,7 +429,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "noise = audio_diffusion.pipe.encode([image], steps=50)"
+    "noise = audio_diffusion.pipe.encode([image])"
    ]
   },
   {
@@ -471,7 +471,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "noise2 = audio_diffusion.pipe.encode([image2], steps=50)"
+    "noise2 = audio_diffusion.pipe.encode([image2], steps=1000)"
    ]
   },
   {
@@ -484,7 +484,6 @@
     "alpha = 0.5  #@param {type:\"slider\", min:0, max:1, step:.1}\n",
     "_, (sample_rate, audio) = audio_diffusion.generate_spectrogram_and_audio(\n",
     "    noise=audio_diffusion.pipe.slerp(noise, noise2, alpha),\n",
-    "    steps=50,\n",
     "    generator=generator)\n",
     "display(Audio(mel.image_to_audio(image), rate=mel.get_sample_rate()))\n",
     "display(Audio(mel.image_to_audio(image2), rate=mel.get_sample_rate()))\n",
@@ -521,7 +520,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.9"
+   "version": "3.10.6"
   },
   "toc": {
    "base_numbering": 1,