import torch
import matplotlib.pyplot as plt
from diffusers import DiffusionPipeline

pipeline = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0",
    dtype=torch.float16,
    device_map="cuda"  # or "mps", "xpu", "cpu"
)

prompts = [
    "Cinematic shot of a cozy coffee shop interior, warm pastel light streaming through a window where a cat rests. Shallow depth of field, glowing cups in soft focus, dreamy lofi-inspired mood, nostalgic tones, framed like a quiet film scene.",
    "Polaroid-style photograph of a cozy coffee shop interior, bathed in warm pastel light. A cat sits on the windowsill near steaming mugs. Soft, slightly faded tones and dreamy blur evoke nostalgia, a lofi mood, and the intimate, imperfect charm of instant film.",
    "Soft watercolor illustration of a cozy coffee shop interior, pastel washes of color filling the space. A cat rests peacefully on the windowsill as warm light glows through. Gentle brushstrokes create a dreamy, lofi-inspired atmosphere with whimsical textures and nostalgic calm.",
    "Isometric pixel-art illustration of a cozy coffee shop interior in detailed 8-bit style. Warm pastel light fills the space as a cat rests on the windowsill. Blocky furniture and tiny mugs add charm, low-res retro graphics enhance the nostalgic, lofi-inspired game aesthetic."
]

images = pipeline(
    prompt=prompts,
).images

fig, axes = plt.subplots(2, 2, figsize=(12, 12))
axes = axes.flatten()

for i, image in enumerate(images):
    axes[i].imshow(image)
    axes[i].set_title(f"Image {i+1}")
    axes[i].axis('off')

plt.tight_layout()
plt.show()

import torch
import matplotlib.pyplot as plt
from diffusers import DiffusionPipeline

pipeline = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0",
    dtype=torch.float16,
    device_map="cuda"  # or "mps", "xpu", "cpu"
)

prompt="""
Isometric pixel-art illustration of a cozy coffee shop interior in detailed 8-bit style. Warm pastel light fills the
space as a cat rests on the windowsill. Blocky furniture and tiny mugs add charm, low-res retro graphics enhance the
nostalgic, lofi-inspired game aesthetic.
"""

images = pipeline(
    prompt=prompt,
    num_images_per_prompt=4
).images

fig, axes = plt.subplots(2, 2, figsize=(12, 12))
axes = axes.flatten()

for i, image in enumerate(images):
    axes[i].imshow(image)
    axes[i].set_title(f"Image {i+1}")
    axes[i].axis('off')

plt.tight_layout()
plt.show()

images = pipeline(
    prompt=prompts,
    num_images_per_prompt=2,
).images

fig, axes = plt.subplots(2, 4, figsize=(12, 12))
axes = axes.flatten()

for i, image in enumerate(images):
    axes[i].imshow(image)
    axes[i].set_title(f"Image {i+1}")
    axes[i].axis('off')

plt.tight_layout()
plt.show()

generator = [torch.Generator(device="cuda").manual_seed(0)] * 3  # or "mps", "xpu", "cpu"

import torch
from diffusers import DiffusionPipeline

pipeline = DiffusionPipeline.from_pretrained(
    "stabilityai/stable-diffusion-xl-base-1.0",
    dtype=torch.float16,
    device_map="cuda"
)

generator = [torch.Generator(device="cuda").manual_seed(i) for i in range(3)]  # or "mps", "xpu", "cpu"
prompts = [
    "Cinematic shot of a cozy coffee shop interior, warm pastel light streaming through a window where a cat rests. Shallow depth of field, glowing cups in soft focus, dreamy lofi-inspired mood, nostalgic tones, framed like a quiet film scene.",
    "Polaroid-style photograph of a cozy coffee shop interior, bathed in warm pastel light. A cat sits on the windowsill near steaming mugs. Soft, slightly faded tones and dreamy blur evoke nostalgia, a lofi mood, and the intimate, imperfect charm of instant film.",
    "Soft watercolor illustration of a cozy coffee shop interior, pastel washes of color filling the space. A cat rests peacefully on the windowsill as warm light glows through. Gentle brushstrokes create a dreamy, lofi-inspired atmosphere with whimsical textures and nostalgic calm.",
    "Isometric pixel-art illustration of a cozy coffee shop interior in detailed 8-bit style. Warm pastel light fills the space as a cat rests on the windowsill. Blocky furniture and tiny mugs add charm, low-res retro graphics enhance the nostalgic, lofi-inspired game aesthetic."
]

images = pipeline(
    prompt=prompts,
    generator=generator
).images

fig, axes = plt.subplots(2, 2, figsize=(12, 12))
axes = axes.flatten()

for i, image in enumerate(images):
    axes[i].imshow(image)
    axes[i].set_title(f"Image {i+1}")
    axes[i].axis('off')

plt.tight_layout()
plt.show()