code: def extract_sequences(x, sequence_length, sequence_stride):
      *batch_shape, signal_length = x.shape
      batch_shape = list(batch_shape)
      x = jnp.reshape(x, (math.prod(batch_shape), signal_length, 1))
      x = jax.lax.conv_general_dilated_patches(
          x,
          (sequence_length,),
          (sequence_stride,),
          "VALID",
          dimension_numbers=("NTC", "OIT", "NTC"),
      )
      return jnp.reshape(x, (*batch_shape, *x.shape[-2:]))
  
imports: import math
  import jax
  import jax.numpy
  from keras.backend import standardize_dtype
  from keras.backend.jax.core import convert_to_tensor
  from keras.utils.module_utils import scipy
label_desc: Use image node_id 7 for calling a global function with example usage: extract_sequences(x, sequence_length, sequence_stride) and returns: jnp