can anyone pls suggest what is the mistake i made from my code pls?
i did all mentioned with guide .
InternalError Traceback (most recent call last)
in
1 tf.random.set_seed(1)
----> 2 a_C = tf.random.normal([1, 1, 4, 4, 3], mean=1, stddev=4)
3 a_G = tf.random.normal([1, 1, 4, 4, 3], mean=1, stddev=4)
4 J_content = compute_content_cost(a_C, a_G)
5 J_content_0 = compute_content_cost(a_C, a_C)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/util/dispatch.py in wrapper(*args, **kwargs)
199 “”“Call target, and fall back on dispatchers if there is a TypeError.”""
200 try:
→ 201 return target(*args, **kwargs)
202 except (TypeError, ValueError):
203 # Note: convert_to_eager_tensor currently raises a ValueError, not a
/usr/local/lib/python3.6/dist-packages/tensorflow/python/ops/random_ops.py in random_normal(shape, mean, stddev, dtype, seed, name)
87 “”"
88 with ops.name_scope(name, “random_normal”, [shape, mean, stddev]) as name:
—> 89 shape_tensor = tensor_util.shape_tensor(shape)
90 mean_tensor = ops.convert_to_tensor(mean, dtype=dtype, name=“mean”)
91 stddev_tensor = ops.convert_to_tensor(stddev, dtype=dtype, name=“stddev”)
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/tensor_util.py in shape_tensor(shape)
1027 # not convertible to Tensors because of mixed content.
1028 shape = tuple(map(tensor_shape.dimension_value, shape))
→ 1029 return ops.convert_to_tensor(shape, dtype=dtype, name=“shape”)
1030
1031
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/ops.py in convert_to_tensor(value, dtype, name, as_ref, preferred_dtype, dtype_hint, ctx, accepted_result_types)
1497
1498 if ret is None:
→ 1499 ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
1500
1501 if ret is NotImplemented:
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in _constant_tensor_conversion_function(v, dtype, name, as_ref)
336 as_ref=False):
337 _ = as_ref
→ 338 return constant(v, dtype=dtype, name=name)
339
340
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in constant(value, dtype, shape, name)
262 “”"
263 return _constant_impl(value, dtype, shape, name, verify_shape=False,
→ 264 allow_broadcast=True)
265
266
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in _constant_impl(value, dtype, shape, name, verify_shape, allow_broadcast)
273 with trace.Trace(“tf.constant”):
274 return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
→ 275 return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
276
277 g = ops.get_default_graph()
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
298 def _constant_eager_impl(ctx, value, dtype, shape, verify_shape):
299 “”“Implementation of eager constant.”""
→ 300 t = convert_to_eager_tensor(value, ctx, dtype)
301 if shape is None:
302 return t
/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/constant_op.py in convert_to_eager_tensor(value, ctx, dtype)
95 except AttributeError:
96 dtype = dtypes.as_dtype(dtype).as_datatype_enum
—> 97 ctx.ensure_initialized()
98 return ops.EagerTensor(value, ctx.device_name, dtype)
99
/usr/local/lib/python3.6/dist-packages/tensorflow/python/eager/context.py in ensure_initialized(self)
537 if self._use_tfrt is not None:
538 pywrap_tfe.TFE_ContextOptionsSetTfrt(opts, self._use_tfrt)
→ 539 context_handle = pywrap_tfe.TFE_NewContext(opts)
540 finally:
541 pywrap_tfe.TFE_DeleteContextOptions(opts)
InternalError: CUDA runtime implicit initialization on GPU:0 failed. Status: out of memory