DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
This office action is responsive to amendment filed on 01/27/2026. Claims 1-20 are pending.
Response to Arguments
In response to applicant’s argument regarding rejection under 35 U.S.C. 101 on page 9, “the elements of amended claim 1 are integrated into a practical application that improves the functioning of specialized hardware by enabling effective strides greater than 1 while operating the computation hardware at stride 1, which results in reduced cost and complexity and simplifies control and buffering requirements. See Specification, [0039]-[0044].”
Examiner respectfully disagrees because any arguably improvements, such as reduced cost and complexity and simplifies control and buffering requirements, are a direct consequence of performing the reformatting of input data and kernel to enable effective stride greater than 1 while operating at stride 1, in which the step of reformatting is characterized as the abstract idea, and MPEP 2106.05(a) “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements.“, where the additional elements recited in the claims, e.g., a system comprising circuitry, a memory, at a high level of generality that amount no more than mere instructions to apply the judicial exception using computer component (see MPEP 2106.05(f)), and the step of receiving data is at most considered as insignificant extra solution activity (e.g., mere data gathering) and determined to be well-understood, routine, and conventional under step 2B (see MPEP 2106.05(d)(II)(i) Receiving or transmitting data over a network).
In response to applicant’s argument regarding rejection under 35 U.S.C. 102 on page 10, “Without conceding the merits of the rejection of independent claims 1 and 17 under 35 U.S.C. § 102-and solely to expedite prosecution-Applicant has amended independent claims 1 and 17. For example, independent claim 1 has been amended to recite, in part, "the sub-maps for each IFM comprising an increased dimensionality with respect to a corresponding IFM and each sub-kernel comprising an increased dimensionality with respect to a corresponding original weight kernel." Independent claim 17 has been amended to include similar features.”
While Examiner agrees that amended claim 1 would overcome the rejection under 35 U.S.C. 102. However, independent claim 17 has not amended to include similar features as recited in amended claim 1. Thus, claim 17 is still rejected under 35 U.S.C. 102, see rejection below.
Specification
The disclosure is objected to because of the following informalities:
[0044] line 4 “the convolvers 404” should be “the convolvers 403” as antecedently described and illustrated in figure 4.
Appropriate correction is required.
Claim Objections
Claims 17-20 objected to because of the following informalities:
Claim 17 line 1 “A method of an apparatus configured to form” should be “A method, performed by an apparatus, configured to form”.
Dependent claims are also objected for inheriting the same deficiencies in which claims they depend on.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to abstract idea without significantly more.
Claim 1 recites an apparatus claim
Under Prong One of Step 2A of the USPTO current eligibility guidance (MPEP 2106), the claim recites limitations that cover mathematical calculations, relationship, and/or formula, such as perform a convolutional layer of a neural network, convolve each sub-map by a corresponding sub-kernel using a horizontal input stride equal to 1 and a vertical input stride equal to 1, each sub-kernel being subdivided from an original weight kernel of a plurality of sets of original weight kernels based on a predetermined horizonal input stride that is greater than 1 and a predetermined vertical input stride that is greater than 1 and each sub-kernel comprising an increased dimensionality with respect to a corresponding original weight kernel, wherein sub-maps for each input feature map (IFM) of a plurality of IFM comprising an increased dimensionality with respect to a corresponding IFM (see at least figure 1 illustrating the convolutional layer in a neural network, which is mathematical layer within a mathematical model, and the step of convolving using window sliding of stride 1 is merely performing mathematical operations such as multiply and accumulate operations on each elements within the sub map and sub kernel. Figures 2-3 further illustrates the concept of dividing sub-kernel based on the predetermined stride that is greater than 1, wherein each sub kernel and each submap having increased dimensionality). Therefore, the claim includes limitations that fall within the “Mathematical Concepts” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Under Prong Two of Step 2A, this judicial exception is not integrated into a practical application. The claim additionally recites a system comprising circuitry, a memory, such additional elements are recited at a high level of generality, e.g., computer components performing computer function of processing and storing data. Furthermore, the claim recites a step of receiving sub-maps for each input feature map (IFM) of a plurality of IFMs, but such step of receiving is also recited at a high level of generality and at most considered as insignificant extra solution activity (e.g., mere data gathering). Such additional elements fail to provide a meaningful limitation on the judicial exception, and amount to no more than mere instructions to apply the exception using computer elements. Thus, the claim is directed to an abstract idea.
Under Step 2B, as discussed with respect to Prong Two of Step 2A, The step of receiving data or a plurality of sub-maps for each input feature map of the plurality of IFMs is considered to be insignificant extra-solution activity in step 2A, and is determined to be well-understood, routine, conventional activity in the field. Court decisions cited in MPEP 2106.05(d)(II) section (i), indicate that mere receiving or transmitting data over a network, is well-understood, routing, conventional function when it is claimed in a merely generic manner. Thus, the additional element fails to ensure the claim as a whole amount to significantly more than the judicial exception itself. Accordingly, the claim is not patent-eligible under 35 U.S.C. 101.
Claim 2 further recite sum a convolved result of each sub-map and the corresponding sub-kernel to form an output feature map (OFM) based on a set of original weight kernels for each set of original weight kernels. Such limitations cover mathematical calculations, relationship, and/or formula (performing accumulation or summing). The claim does not recite additional element that would integrate the judicial exception into a practical application under step 2A prong two or ensure the claim as a whole amount to significantly more than the judicial exception itself under step 2B. Accordingly, the claim is not patent-eligible under 35 U.S.C. 101.
Claim 3 further recites subdividing each original weight kernel of the plurality of sets of the original weight kernels based on the predetermined horizontal input stride and the predetermined vertical input stride to form sub-kernels for each original weight kernel, such limitations cover mathematical calculations, relationship, and/or formula (figures 2-3 illustrates the concept of reformatting the original data by subdividing data based on the predetermined stride value. Thus, such concept falls under the mathematical relationship). Moreover, the claim recites a weight-kernel subdivider at a high level of generality, e.g., computer component performing computer function, which amounts to no more than mere instructions to apply the judicial exception using computer component. Thus, the claim does not recite additional element that would integrate the judicial exception into a practical application under step 2A prong two or ensure the claim as a whole amount to significantly more than the judicial exception itself under step 2B. Accordingly, the claim is not patent-eligible under 35 U.S.C. 101.
Claim 4 further recites wherein a weight in a sub-kernel comprises a weight in the original weight kernel from which the sub-kernel was subdivided based on a modulo of the predetermined horizontal input stride and based on a modulo of the predetermined vertical input stride of a position of the weight in the original weight kernel, such limitations cover mathematical calculations, relationship, and/or formula (such limitation describes the weight in a sub-kernel, which was subdivided based on a modulo of predetermined stride). The claim does not recite additional element that would integrate the judicial exception into a practical application under step 2A prong two or ensure the claim as a whole amount to significantly more than the judicial exception itself under step 2B. Accordingly, the claim is not patent-eligible under 35 U.S.C. 101.
Claim 5 further recites subdivide each of the plurality of IFMs based on the predetermined horizontal input stride and the predetermined vertical input stride to form the sub-maps for each IFM of the plurality of IFMs. Such limitations cover mathematical calculations, relationship, and/or formula (figures 2-3 illustrates the concept of reformatting the original data by subdividing data based on the predetermined stride value. thus, such concept falls under the mathematical relationship). Moreover, the claim recites an IFM-subdivider at a high level of generality, e.g., computer component performing computer function, which amounts to no more than mere instructions to apply the judicial exception using computer component. The claim does not recite additional element that would integrate the judicial exception into a practical application under step 2A prong two or ensure the claim as a whole amount to significantly more than the judicial exception itself under step 2B. Accordingly, the claim is not patent-eligible under 35 U.S.C. 101.
Claim 6 further recites the predetermined horizontal input stride and the predetermined vertical input stride are equal to a predetermined second value, subdivide each original weight kernel of a plurality of sets of original weight kernels by a square of the predetermined second value to form a plurality of sub-kernels for each set of original weight kernels, and subdivide each of the plurality of IFMs based on the square of the predetermined second value to form the plurality of sub-maps for each IFM of the plurality of IFMs. Such limitations cover mathematical calculations, relationship, and/or formula (see figures 2-3 [0028] describes dividing of original kernel and input IFM into square of 2 or 3). The claim does not recite additional element that would integrate the judicial exception into a practical application under step 2A prong two or ensure the claim as a whole amount to significantly more than the judicial exception itself under step 2B. Accordingly, the claim is not patent-eligible under 35 U.S.C. 101.
Claim 7 further recites a domain converter coupled to the weight-kernel subdivider and the IFM subdivider, the domain converter being configured to convert elements of each sub-map into a Winograd domain. The limitation of converting elements of each submap into a Winograd domain cover mathematical calculations, relationship, and/or formula (the step of converting is a mathematical operation to convert data from one domain to another domain). The limitation domain converter coupled to the weight-kernel subdivider and the IFM subdivider is recited at a high level of generality, e.g., computer components performing computer function of performing operation and amount to no more than mere instructions to apply the judicial exception using computer components. Thus, the additional elements do not integrate the judicial exception into a practical application under step 2A prong two or provide an inventive concept under step 2B. Accordingly, the claim is not patent-eligible under 35 U.S.C. 101.
Claim 8 further recites wherein the predetermined horizontal input stride is 2 and the predetermined vertical input stride is 2, or the predetermined horizontal input stride is 3 and the predetermined vertical input stride is 3. Such limitations cover mathematical calculations, relationship, and/or formula (such as describing the value of predetermined input stride to be performed). The claim does not recite additional element that would integrate the judicial exception into a practical application under step 2A prong two or ensure the claim as a whole amount to significantly more than the judicial exception itself under step 2B. Accordingly, the claim is not patent-eligible under 35 U.S.C. 101.
Claims 9-16 recite apparatus claims having similar limitation as the apparatus claims 1-8. Thus, they are rejected for the same reasons.
Claims 17-20 recite method claims that would be practiced by the apparatus claims 1-5, 7. Thus, they are rejected for the same reasons.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 17-18 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by (Lele - US 20180032857).
Regarding claim 17, Lele teaches a method of an apparatus configured to form at least one output feature map (OFM) from at least one input feature map (IFM) at a convolutional layer in a neural network (Lele [0007] describes a method and implementing a convolutional neural network accelerator [i.e., an apparatus] to execute CNN algorithm and [0011] describes CNN applications implements convolution backpropagation layers [i.e., a convolutional layer] [i.e., a convolutional layer in a neural network] to form at least one OFM from at least one IFM. See at least figure 6C ), the method comprising, comprising receiving, by the apparatus, sub-maps for each input feature map (IFM) of a plurality of IFMs, and (Lele, wherein figure 6C illustrates the input matrix [i.e., each input feature map] is received and comprises a plurality of sub matrices 2x2 (such as first sub-matrix is 0,0,0,1, second sub-matrix is 0,0,1,2, and so far) for performing dot product in the convolution, thus such sub matrices corresponding to a plurality of sub-maps, and multiple convolution backpropagation layers are implemented on a plurality of backpropagation input [i.e., a plurality of IFMs]) convolving, by the apparatus, each sub-map by a corresponding sub-kernel using a horizontal input stride equal to 1 and a vertical input stride equal to 1 (Lele figure 6C illustrates each submap 2x2 is convolved with an extracted convolution 2x2 filter [i.e., a corresponding sub-kernel] based on a stride of 1 to generate the backpropagation output matrix. For example, a 2x2 sub map contains 0,0,0,1 is convolved with 11,9,3,1 to generate output 1 as the first row first column, then the next 2x2 sub-map contains 0,0,1,2 is convolved with 11,9,3,1 to generate 5 as first row second column, and so on), each sub-kernel being subdivided from an original weight kernel of a plurality of sets of original weight kernels based on a predetermined horizonal input stride that is greater than 1 and a predetermined vertical input stride that is greater than 1 (Lele, figure 6B illustrates each sub-kernel 611’,612’,613’,614’ [i.e., each sub-kernel] being divided from an original kernel matrix 600 [i.e., an original weight kernel] as illustrated in figure 6A. [0011] describes CNN implements a plurality of convolution backpropagation layers, thus a plurality of sets of weight kernels are required. [0054] describes the original filter is divided into (stride)x(stride) blocks, which are smaller filters that are extracted based on stride and [0055] describes that figure 6A illustrates extraction of a two-dimensional filter with stride 2. [0045] describes that the characteristics of CNN accelerator is identified, wherein the characteristics includes sizes and coefficient of filters and strides and [0061] describes that the characteristics of the backpropagation layers are identified in advanced. Accordingly, the original kernel matrix 600 is divided into sub-kernel based on a predetermined horizontal input stride of 2 and vertical stride of 2, which is greater than 1).
Regarding claim 18, Lele teaches the neural network of claim 17, further comprising summing, by the apparatus, convolved result of each sub-map and the corresponding sub-kernel to form an output feature map (OFM) corresponding to a set of original weight kernels for each set of original weight kernels (Lele figure 6C illustrates the convolution layer configured to sum a multiplication of result of each pair of elements of each submap and corresponding sub-kernel to form an output matrix [i.e., an output feature map] corresponding to the original set weight 600 for each set of weights kernel in the convolution backpropagation layers. For example, first sub map 0,0,0,1 is performed dot product with 11,9,3,1, which is equivalent to 0+0+0+1 =1 and second sub map 0,0,1,2 is performed dot product with 11,9,3,1, which is equivalent to 0+0+3+2 = 5, and third sub map 0,0,2,0 is performed dot product with 11,9,3,1, which is equivalent to 0+0+6+0 = 6 and so on with a stride of 1 horizontal and vertical ).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HUY DUONG whose telephone number is (571)272-2764. The examiner can normally be reached Mon-Friday 7:30-5:30.
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/HUY DUONG/Examiner, Art Unit 2183 (571)272-2764
/ANDREW CALDWELL/Supervisory Patent Examiner, Art Unit 2182
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