import svetoviz_webgpu as sv

# 1. Prepare compressed 1D latent data (Batch, Channels, Length)
latent_length = 64
latent_data = torch.randn(1, 16, latent_length)

# 2. Define the Transpose 1D Convolutional module
conv_t1d = nn.ConvTranspose1d(in_channels=16, out_channels=8, kernel_size=4, stride=2, padding=1)

def terminal_callback(buffer, message, images, files):
    # 3. Process the latent vector through the module
    output = conv_t1d(latent_data)

    # Log the upsampled shape to the Svetoviz terminal
    buffer.send_system_message(f"Upsampled signal. Output shape: {list(output.shape)}")

# 4. Start the interactive session
sv.pytorch_web(module=conv_t1d, terminal_callback=terminal_callback)