Boosted Trees: delay switching to version 2 cond (even when running in v1).
This is breaking some tests. Delaying until we have a fix. PiperOrigin-RevId: 257199240
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@ -1217,7 +1217,7 @@ class ConditionalAccumulatorBase(object):
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if name is None:
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if name is None:
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name = "%s_NumAccumulated" % self._name
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name = "%s_NumAccumulated" % self._name
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if compat.forward_compatible(2019, 7, 8):
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if compat.forward_compatible(2019, 8, 8):
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return gen_data_flow_ops.resource_accumulator_num_accumulated(
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return gen_data_flow_ops.resource_accumulator_num_accumulated(
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self._accumulator_ref, name=name)
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self._accumulator_ref, name=name)
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@ -1237,7 +1237,7 @@ class ConditionalAccumulatorBase(object):
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Returns:
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Returns:
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Operation that sets the accumulator's time step.
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Operation that sets the accumulator's time step.
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"""
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"""
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if compat.forward_compatible(2019, 7, 8):
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if compat.forward_compatible(2019, 8, 8):
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return gen_data_flow_ops.resource_accumulator_set_global_step(
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return gen_data_flow_ops.resource_accumulator_set_global_step(
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self._accumulator_ref,
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self._accumulator_ref,
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math_ops.cast(ops.convert_to_tensor(new_global_step), _dtypes.int64),
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math_ops.cast(ops.convert_to_tensor(new_global_step), _dtypes.int64),
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@ -1276,7 +1276,7 @@ class ConditionalAccumulator(ConditionalAccumulatorBase):
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name: Optional name for the accumulator.
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name: Optional name for the accumulator.
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reduction_type: Reduction type to use when taking the gradient.
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reduction_type: Reduction type to use when taking the gradient.
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"""
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"""
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if compat.forward_compatible(2019, 7, 8):
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if compat.forward_compatible(2019, 8, 8):
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accumulator_ref = gen_data_flow_ops.resource_conditional_accumulator(
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accumulator_ref = gen_data_flow_ops.resource_conditional_accumulator(
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dtype=dtype,
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dtype=dtype,
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shape=shape,
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shape=shape,
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@ -1316,7 +1316,7 @@ class ConditionalAccumulator(ConditionalAccumulatorBase):
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grad.get_shape().assert_is_compatible_with(self._shape)
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grad.get_shape().assert_is_compatible_with(self._shape)
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local_step = math_ops.cast(ops.convert_to_tensor(local_step), _dtypes.int64)
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local_step = math_ops.cast(ops.convert_to_tensor(local_step), _dtypes.int64)
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if compat.forward_compatible(2019, 7, 8):
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if compat.forward_compatible(2019, 8, 8):
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return gen_data_flow_ops.resource_accumulator_apply_gradient(
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return gen_data_flow_ops.resource_accumulator_apply_gradient(
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self._accumulator_ref,
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self._accumulator_ref,
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local_step=local_step,
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local_step=local_step,
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@ -1347,7 +1347,7 @@ class ConditionalAccumulator(ConditionalAccumulatorBase):
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Raises:
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Raises:
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InvalidArgumentError: If num_required < 1
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InvalidArgumentError: If num_required < 1
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"""
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"""
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if compat.forward_compatible(2019, 7, 8):
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if compat.forward_compatible(2019, 8, 8):
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out = gen_data_flow_ops.resource_accumulator_take_gradient(
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out = gen_data_flow_ops.resource_accumulator_take_gradient(
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self._accumulator_ref, num_required, dtype=self._dtype, name=name)
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self._accumulator_ref, num_required, dtype=self._dtype, name=name)
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else:
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else:
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