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Update app.py
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app.py
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@@ -32,15 +32,6 @@ from flax.training.common_utils import shard
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def create_key(seed=0):
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return jax.random.PRNGKey(seed)
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def image_grid(imgs, rows, cols):
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w, h = imgs[0].size
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grid = Image.new("RGB", size=(cols * w, rows * h))
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for i, img in enumerate(imgs):
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grid.paste(img, box=(i % cols * w, i // cols * h))
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return grid
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# load control net and stable diffusion v1-5
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controlnet, controlnet_params = FlaxControlNetModel.from_pretrained(
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"learner/jax-diffuser-event", from_flax=True, dtype=jnp.float32
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@@ -62,7 +53,7 @@ def infer(prompts, negative_prompts, image):
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num_samples = 1 # jax.device_count()
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rng = create_key(0)
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rng = jax.random.split(rng, jax.device_count())
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battlemap_image =
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prompt_ids = pipe.prepare_text_inputs([prompts] * num_samples)
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negative_prompt_ids = pipe.prepare_text_inputs([negative_prompts] * num_samples)
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def create_key(seed=0):
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return jax.random.PRNGKey(seed)
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# load control net and stable diffusion v1-5
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controlnet, controlnet_params = FlaxControlNetModel.from_pretrained(
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"learner/jax-diffuser-event", from_flax=True, dtype=jnp.float32
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num_samples = 1 # jax.device_count()
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rng = create_key(0)
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rng = jax.random.split(rng, jax.device_count())
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battlemap_image = Image.open(image)
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prompt_ids = pipe.prepare_text_inputs([prompts] * num_samples)
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negative_prompt_ids = pipe.prepare_text_inputs([negative_prompts] * num_samples)
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