Fix regression caused by PR #1868
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@ -255,16 +255,14 @@ def tf_pick_value_from_range(value_range, clock=None, double_precision=False):
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tf.minimum(tf.constant(1.0, dtype=tf.float64), clock),
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tf.minimum(tf.constant(1.0, dtype=tf.float64), clock),
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)
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)
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value = value_range.start + clock * (value_range.end - value_range.start)
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value = value_range.start + clock * (value_range.end - value_range.start)
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if value_range.r:
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# sample the value from a uniform distribution with "radius" <r>
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# if the option <r> (<value>~<r>, randomization radius) is supplied,
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value = tf.random.stateless_uniform(
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# sample the value from a uniform distribution with "radius" <r>
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[],
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value = tf.random.stateless_uniform(
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minval=value - value_range.r,
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[],
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maxval=value + value_range.r,
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minval=value - value_range.r,
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seed=(clock * tf.int32.min, clock * tf.int32.max),
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maxval=value + value_range.r,
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dtype=tf.float64,
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seed=(clock * tf.int32.min, clock * tf.int32.max),
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)
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dtype=tf.float64,
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)
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if isinstance(value_range.start, int):
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if isinstance(value_range.start, int):
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return tf.cast(tf.math.round(value), tf.int64 if double_precision else tf.int32)
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return tf.cast(tf.math.round(value), tf.int64 if double_precision else tf.int32)
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return tf.cast(value, tf.float64 if double_precision else tf.float32)
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return tf.cast(value, tf.float64 if double_precision else tf.float32)
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