inferpy.util package¶
Submodules¶
inferpy.util.error module¶
Module implementing custom exceptions and errors
inferpy.util.format module¶
Module implementing text formatting operaionts
inferpy.util.ops module¶
Module implementing some useful operations over tensors and random variables
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inferpy.util.ops.
case
(d, default=None, exclusive=True, strict=False, name='case')[source]¶ Control flow operation depending of the outcome of a tensor. Any expression in tensorflow giving as a result a boolean is allowed as condition.
Internally, the operation tensorflow.case is invoked. Unlike the tensorflow operation, this one accepts InferPy variables as input parameters.
Parameters: - d – dictionary where the keys are the conditions (i.e. boolean tensor).
- exclusive – True iff at most one case is allowed to evaluate to True.
- name – name of the resulting tensor.
Returns: Tensor implementing the case operation. This is the output of the operation tensorflow.case internally invoked.
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inferpy.util.ops.
case_states
(var, d, default=None, exclusive=True, strict=False, name='case')[source]¶ Control flow operation depending of the outcome of a discrete variable.
Internally, the operation tensorflow.case is invoked. Unlike the tensorflow operation, this one accepts InferPy variables as input parameters.
Parameters: - var – Control InferPy discrete random variable.
- d – dictionary where the keys are each of the possible values of control variable
- the values are returning tensors for each case. (and) –
- exclusive – True iff at most one case is allowed to evaluate to True.
- name – name of the resulting tensor.
Returns: Tensor implementing the case operation. This is the output of the operation tensorflow.case internally invoked.
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inferpy.util.ops.
dot
(x, y)[source]¶ Compute dot product between an InferPy or Tensor object. The number of batches N equal to 1 for one of them, and higher for the other one.
If necessarily, the order of the operands may be changed.
- Args:
- x: first operand. This could be an InferPy variable, a Tensor, a numpy object or a numeric Python list. x: second operand. This could be an InferPy variable, a Tensor, a numpy object or a numeric Python list.
- Retruns:
- An InferPy variable of type Deterministic encapsulating the resulting tensor of the multiplications.
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inferpy.util.ops.
fix_shape
(s)[source]¶ Transforms a shape list into a standard InferPy shape format.
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inferpy.util.ops.
gather
(params, indices, validate_indices=None, name=None, axis=0)[source]¶ Operation for selecting some of the items in a tensor.
Internally, the operation tensorflow.gather is invoked. Unlike the tensorflow operation, this one accepts InferPy variables as input parameters.
Parameters: - params – A Tensor. The tensor from which to gather values. Must be at least rank axis + 1.
- indices – A Tensor. Must be one of the following types: int32, int64. Index tensor. Must be in range
- params.shape[axis]) ([0,) –
- axis – A Tensor. Must be one of the following types: int32, int64. The axis in params to gather indices
- Defaults to the first dimension. Supports negative indexes. (from.) –
- name – A name for the operation (optional).
Returns: A Tensor. Has the same type as params.. This is the output of the operation tensorflow.gather internally invoked.
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inferpy.util.ops.
matmul
(a, b, transpose_a=False, transpose_b=False, adjoint_a=False, adjoint_b=False, a_is_sparse=False, b_is_sparse=False, name=None)[source]¶ Matrix multiplication.
Input objects may be tensors but also InferPy variables.
Parameters: - a – Tensor of type float16, float32, float64, int32, complex64, complex128 and rank > 1.
- b – Tensor with same type and rank as a.
- transpose_a – If True, a is transposed before multiplication.
- transpose_b – If True, b is transposed before multiplication.
- adjoint_a – If True, a is conjugated and transposed before multiplication.
- adjoint_b – If True, b is conjugated and transposed before multiplication.
- a_is_sparse – If True, a is treated as a sparse matrix.
- b_is_sparse – If True, b is treated as a sparse matrix.
- name – Name for the operation (optional).
- Retruns:
- An InferPy variable of type Deterministic encapsulating the resulting tensor of the multiplications.
inferpy.util.runtime module¶
Module with useful definitions to be used in runtime
inferpy.util.wrappers module¶
Module with useful wrappers used for the development of InferPy.
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inferpy.util.wrappers.
input_model_data
(f)[source]¶ wrapper that transforms, if required, a dataset object, making it suitable for InferPy inference process.
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inferpy.util.wrappers.
multishape
(f)[source]¶ This wrapper allows to apply a function with simple parameters, over multidimensional ones.