code: def tensors_in_support(
      draw, support, batch_shape=None, event_dim=None, dtype=np.float32
  ):
      """Strategy for drawing Tensors in the given support.
  
      Supports have a notion of event shape, which is the trailing dimensions in
      which the support region may not be axis-aligned (e.g., the event ndims of
      `VECTOR_STRICTLY_INCREASING` is 1).  This strategy produces Tensors with at
      least the support's event rank, and also an optional batch shape.
  
      Args:
        draw: Hypothesis strategy sampler supplied by `@hps.composite`.
        support: The `Support` in which the Tensor should live.
        batch_shape: Optional shape.  The returned Tensors will have this batch
          shape.  Hypothesis will pick one if omitted.
        event_dim: Optional Python int giving the size of each event dimension.
          This is shared across all event dimensions, permitting square event
          matrices, etc. If omitted, Hypothesis will choose one.
        dtype: DType to use in generating tensor data.
          Default value: `np.float32`.
  
      Returns:
        tensors: A strategy for drawing such Tensors.
      """
      if event_dim is None:
          event_dim = draw(hps.integers(min_value=2, max_value=6))
      if batch_shape is None:
          batch_shape = tensorshape_util.as_list(draw(shapes()))
      shape = batch_shape + [event_dim] * min_rank_for_support(support)
      constraint_fn = constrainer(support)
      return draw(
          constrained_tensors(constraint_fn, shape, dtype=dtype)
      )
  
imports: import contextlib
  import os
  import re
  import traceback
  import unittest
  import hypothesis
  from hypothesis.extra import numpy
  import hypothesis.strategies
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.util.deferred_tensor import DeferredTensor
label_desc: Use image node_id 19 for calling a global function with example usage: tensors_in_support(draw, support, batch_shape, event_dim, dtype) and returns: draw