refixes","emptyStyle","vendorProps","finalPropName","final","cssProps","capName","vendorPropName","rdisplayswap","cssShow","visibility","cssNormalTransform","letterSpacing","fontWeight","setPositiveNumber","subtract","max","boxModelAdjustment","dimension","box","isBorderBox","styles","computedVal","extra","delta","ceil","getWidthOrHeight","valueIsBorderBox","offsetProp","getClientRects","Tween","easing","cssHooks","opacity","animationIterationCount","columnCount","fillOpacity","flexGrow","flexSh...

refixes","emptyStyle","vendorProps","finalPropName","final","cssProps","capName","vendorPropName","rdisplayswap","cssShow","visibility","cssNormalTransform","letterSpacing","fontWeight","setPositiveNumber","subtract","max","boxModelAdjustment","dimension","box","isBorderBox","styles","computedVal","extra","delta","ceil","getWidthOrHeight","valueIsBorderBox","offsetProp","getClientRects","Tween","easing","cssHooks","opacity","animationIterationCount","columnCount","fillOpacity","flexGrow","flexSh...

The elements can be addressed by integer <a href="#Index_expressions">indices</a>
0 through <code>len(a)-1</code>.
Array types are always one-dimensional but may be composed to form
multi-dimensional types.
</p>

<pre>
[32]byte
[2*N] struct { x, y int32 }
[1000]*float64
[3][5]int
[2][2][2]float64  // same as [2]([2]([2]float64))
</pre>

        InvalidArgument("Node ", node->name(), " was not found in the graph");
    return -1;
  }

  tensorflow::shape_inference::ShapeHandle shape = ic->output(output.index);

  // Unknown rank means the number of dimensions is -1.
  if (!ic->RankKnown(shape)) {
    return -1;
  }

  return ic->Rank(shape);
}

void TF_GraphGetTensorShape(TF_Graph* graph, TF_Output output, int64_t* dims,